A deep learning-based reconstruction of cosmic ray-induced air showers
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F18%3A00547191" target="_blank" >RIV/68378271:_____/18:00547191 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1016/j.astropartphys.2017.10.006" target="_blank" >https://doi.org/10.1016/j.astropartphys.2017.10.006</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.astropartphys.2017.10.006" target="_blank" >10.1016/j.astropartphys.2017.10.006</a>
Alternative languages
Result language
angličtina
Original language name
A deep learning-based reconstruction of cosmic ray-induced air showers
Original language description
We describe a method of reconstructing air showers induced by cosmic rays using deep learning techniques. We simulate an observatory consisting of ground-based particle detectors with fixed locations on a regular grid. The detector's responses to traversing shower particles are signal amplitudes as a function of time, which provide information on transverse and longitudinal shower properties. In order to take advantage of convolutional network techniques specialized in local pattern recognition, we convert all information to the image-like grid of the detectors. In this way, multiple features, such as arrival times of the first particles and optimized characterizations of time traces, are processed by the network. The reconstruction quality of the cosmic ray arrival direction turns out to be competitive with an analytic reconstruction algorithm. The reconstructed shower direction, energy and shower depth show the expected improvement in resolution for higher cosmic ray energy.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10303 - Particles and field physics
Result continuities
Project
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Continuities
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Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Astroparticle Physics
ISSN
0927-6505
e-ISSN
1873-2852
Volume of the periodical
97
Issue of the periodical within the volume
January
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
8
Pages from-to
46-53
UT code for WoS article
000423640700007
EID of the result in the Scopus database
2-s2.0-85034647911