Event-by-event reconstruction of the shower maximum Xmax with the Surface Detector of the Pierre Auger Observatory using deep learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F22%3A00564879" target="_blank" >RIV/68378271:_____/22:00564879 - isvavai.cz</a>
Alternative codes found
RIV/61989592:15310/22:73616949
Result on the web
<a href="https://pos.sissa.it/395/359/pdf" target="_blank" >https://pos.sissa.it/395/359/pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.22323/1.395.0359" target="_blank" >10.22323/1.395.0359</a>
Alternative languages
Result language
angličtina
Original language name
Event-by-event reconstruction of the shower maximum Xmax with the Surface Detector of the Pierre Auger Observatory using deep learning
Original language description
The measurement of the mass composition of ultra-high energy cosmic rays constitutes a prime challenge in astroparticle physics. Most detailed information on the composition can be obtained from measurements of the depth of maximum of air showers, Xmax, with the use of fluorescence telescopes, which can be operated only during clear and moonless nights. Using deep neural networks, it is now possible for the first time to perform an event-by-event reconstruction of Xmax with the Surface Detector (SD) of the Pierre Auger Observatory. Therefore, previously recorded data can be analyzed for information on Xmax, and thus, the cosmic-ray composition. Since the SD operates with a duty cycle of almost 100% and its event selection is less strict than for the Fluorescence Detector (FD), the gain in statistics with respect to the FD is almost a factor of 15 for energies above 1019.5 eV.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10303 - Particles and field physics
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of Science
ISBN
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ISSN
1824-8039
e-ISSN
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Number of pages
12
Pages from-to
359
Publisher name
Sissa Medilab srl
Place of publication
Trieste
Event location
Berlin
Event date
Jul 12, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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