EPJ Web Conf.
Volume 191, 2018XXth International Seminar on High Energy Physics (QUARKS-2018)
|Number of page(s)||6|
|Section||Cosmology and Astroparticle Physics|
|Published online||31 October 2018|
Ultra-high-energy cosmic rays mass composition studies with the Telescope Array Surface Detector data
Institute for Nuclear Research of the Russian Academy of Sciences, 60th October Anniversary st. 7a, 117312, Moscow, Russia
2 Faculty of Physics, Lomonosov Moscow State University, 119991, Moscow, Russia
* e-mail: email@example.com
Published online: 31 October 2018
The results on ultra-high energy cosmic rays’ chemical composition based on the data from the Telescope Array surface detector are reported. The analysis is based the boosted decision tree (BDT) multivariate analysis built upon 14 observables related to both the properties of the shower front and the lateral distribution function. The multivariate classifier is trained with Monte-Carlo sets: proton-induced, which is considered as background events, and ironinduced, considered as signal events. The classifier results in a single variable ξ for data and Monte-Carlo sets, available for one-dimensional analysis. The data to Monte-Carlo comparison results in an average atomic mass of UHECR for energy range 1018:0 - 1020:0 eV. The average atomic mass of primary particles corresponds to 〈ln A〉 = 1:52± 0:08(stat.)± 0:1(syst.). The comparison with TA hybrid composition results and the other experiments is presented.
© The Authors, published by EDP Sciences, 2018
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