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Identification of patterns in cosmic-ray arrival directions using dynamic graph convolutional neural networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F21%3A00539716" target="_blank" >RIV/68378271:_____/21:00539716 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.astropartphys.2020.102527" target="_blank" >https://doi.org/10.1016/j.astropartphys.2020.102527</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.astropartphys.2020.102527" target="_blank" >10.1016/j.astropartphys.2020.102527</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Identification of patterns in cosmic-ray arrival directions using dynamic graph convolutional neural networks

  • Original language description

    We present a new approach for the identification of ultra-high energy cosmic rays from sources using dynamic graph convolutional neural networks. These networks are designed to handle sparsely arranged objects and to exploit their short- and long-range correlations. Our method searches for patterns in the arrival directions of cosmic rays, which are expected to result from coherent deflections in cosmic magnetic fields. The network discriminates astrophysical scenarios with source signatures from those with only isotropically distributed cosmic rays and allows for the identification of cosmic rays that belong to a deflection pattern. We use simulated astrophysical scenarios where the source density is the only free parameter to show how density limits can be derived. We apply this method to a public data set from the AGASA Observatory.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10303 - Particles and field physics

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2021

  • 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

  • Volume of the periodical

    126

  • Issue of the periodical within the volume

    Mar

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    10

  • Pages from-to

    1-10

  • UT code for WoS article

    000600571200006

  • EID of the result in the Scopus database

    2-s2.0-85096862548