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Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

Abstract:

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural net...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted manuscript

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Publisher copy:
10.1088/1748-0221/12/03/P03011

Authors


Acciarri, R More by this author
More by this author
Department:
Oxford, MPLS, Physics, Particle Physics
More by this author
Department:
Oxford, MPLS, Physics, Particle Physics
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U.S. Department of Energy More from this funder
U.S. National Science Foundation More from this funder
Swiss National Science Foundation More from this funder
Science and Technology Facilities Council More from this funder
Royal Society More from this funder
Publisher:
Institute of Physics Publisher's website
Journal:
Journal of Instrumentation Journal website
Volume:
7
Pages:
P03011
Publication date:
2017-03-24
Acceptance date:
2017-02-28
DOI:
Pubs id:
pubs:660294
URN:
uri:baa86ba5-6404-48d1-9556-86ef3543c18a
UUID:
uuid:baa86ba5-6404-48d1-9556-86ef3543c18a
Local pid:
pubs:660294

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