Mass composition anisotropy with the TA SD data


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Discussion timeslot (ZOOM-Meeting): 13. July 2021 - 18:00
ZOOM-Meeting URL:
ZOOM-Meeting ID: 92210078166
ZOOM-Meeting Passcode: ICRC2021
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'Mass composition anisotropy is predicted by a number of theories describing sources of ultra-high-energy cosmic rays. rnEvent-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. rnIn the present study we propose to employ the observable $xi$ used in the mass composition analysis of the Telescope Array surface detector (TA SD) data for the mass composition anisotropy analysis. rnThe $xi$ variable is determined with the use of Boosted Decision Trees (BDT) technique trained with the Monte-Carlo sets, and the $xi$ value is assigned for each event, where $xi=1$ corresponds to an event initiated by the primary iron nuclei and $xi=-1$ corresponds to a proton event.rnUse of $xi$ 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. rnResults for the TA SD 12-year data set mass composition anisotropy will be presented and possible applications for the cosmic-ray source models will be discussed. This presentation contains results we would like to include in a TA highlight talk.'

Authors: Yana Zhezher
Collaboration: Telescope Array

Indico-ID: 299
Proceeding URL:

Presenter: Yana Zhezher

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