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Title:Mass composition anisotropy with the Telescope Array Surface Detector data
Authors:ID Zhezher, Y. (Author)
ID Lundquist, Jon Paul (Author), et al.
Files:.pdf ICRC2021_299.pdf (1,14 MB)
MD5: 0E101608760E103960110EA18E240713
 
URL https://pos.sissa.it/395/299/
 
URL https://pos.sissa.it/395/299/pdf
 
Language:English
Work type:Not categorized
Typology:1.08 - Published Scientific Conference Contribution
Organization:UNG - University of Nova Gorica
Abstract:Mass composition anisotropy is predicted by a number of theories describing sources of ultra-high-energy cosmic rays. Event-by-event determination of a type of a primary cosmic-ray particle is impossible due to large shower-to-shower fluctuations, and the mass composition usually is obtained by averaging over some composition-sensitive observable determined independently for each extensive air shower (EAS) over a large number of events. In the present study we propose to employ the observable ξ used in the TA mass composition analysis for the mass composition anisotropy analysis. The ξ variable is determined with the use of Boosted Decision Trees (BDT) technique trained with the Monte-Carlo sets, and the ξ value is assigned for each event, where ξ=1 corresponds to an event initiated by the primary iron nuclei and ξ=−1 corresponds to a proton event. Use of ξ distributions obtained for the Monte-Carlo sets allows us to separate proton and iron candidate events from a data set with some given accuracy and study its distributions over the observed part of the sky. Results for the TA SD 11-year data set mass composition anisotropy will be presented.
Keywords:Telescope Array, indirect detection, surface detection, ground array, ultra-high energy, cosmic rays, composition, anisotropy, machine learning, boosted decision tree
Publication status:Published
Year of publishing:2022
PID:20.500.12556/RUNG-8525 New window
COBISS.SI-ID:166984451 New window
DOI:10.22323/1.395.0299 New window
NUK URN:URN:SI:UNG:REP:AQHSIAFL
Publication date in RUNG:04.10.2023
Views:1965
Downloads:7
Metadata:XML DC-XML DC-RDF
:
ZHEZHER, Y. and LUNDQUIST, Jon Paul, 2022, Mass composition anisotropy with the Telescope Array Surface Detector data. In : 37th International Cosmic Ray Conference [online]. Published Scientific Conference Contribution. Trieste, Italy. 2022. [Accessed 11 April 2025]. Retrieved from: https://repozitorij.ung.si/IzpisGradiva.php?lang=eng&id=8525
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Record is a part of a monograph

Title:37th International Cosmic Ray Conference : ICRC2023
Place of publishing:Trieste, Italy
Publisher:Proceedings of Science
Year of publishing:2022

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License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
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