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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. |
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Title |
Neutrino interaction classification with a convolutional neural network in the DUNE far detector |
Type |
Journal Article |
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Year |
2020 |
Publication |
Physical Review D |
Abbreviated Journal  |
Phys. Rev. D |
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Volume |
102 |
Issue |
9 |
Pages |
092003 - 20pp |
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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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Address |
[Decowski, M. P.; De Jong, P.] Univ Amsterdam, NL-1098 XG Amsterdam, Netherlands, Email: saul.alonso.monsalve@cern.ch; |
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Publisher |
Amer Physical Soc |
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English |
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Series Issue |
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Edition |
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ISSN |
2470-0010 |
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Conference |
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Notes |
WOS:000587596500004 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4598 |
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Author |
Masud, M.; Bishai, M.; Mehta, P. |
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Title |
Extricating New Physics Scenarios at DUNE with Higher Energy Beams |
Type |
Journal Article |
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Year |
2019 |
Publication |
Scientific Reports |
Abbreviated Journal |
Sci Rep |
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Volume |
9 |
Issue |
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Pages |
352 - 9pp |
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Keywords |
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Abstract |
The proposed Deep Underground Neutrino Experiment (DUNE) utilizes a wide-band on-axis tunable muon-(anti) neutrino beam with a baseline of 1300 km to search for CP violation with high precision. Given the long baseline, DUNE is also sensitive to effects due to matter induced non-standard neutrino interactions (NSI) which can interfere with the standard three-flavor oscillation paradigm. Hence it is desirable to design strategies to disentangle effects due to NSI from standard oscillations. In this article, we exploit the tunability of the DUNE neutrino beam over a wide-range of energies to devise an experimental strategy for separating oscillation effects due to NSI from the standard three-flavor oscillation scenario. Using chi(2) analysis, we obtain an optimal combination of beam tunes and distribution of run times in neutrino and anti-neutrino modes that would enable DUNE to isolate new physics scenarios from the standard. We can distinguish scenarios at 3 sigma (5 sigma) level for almost all (similar to 50%) values of delta. To the best of our knowledge, our strategy is entirely new and has not been reported elsewhere. |
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Address |
[Masud, Mehedi] Univ Valencia, CSIC, Inst Fis Corpuscular, Astroparticle & High Energy Phys Grp, Parc Cient Paterna,C Catedrat Jose Beltran 2E, E-46980 Valencia, Spain, Email: masud@ific.uv.es; |
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Publisher |
Nature Publishing Group |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2045-2322 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000456392400033 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3891 |
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