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Astrophysics > High Energy Astrophysical Phenomena

Title: Honing cross-correlation tools for inference on ultra-high-energy cosmic-ray composition

Abstract: The chemical composition of the highest-energy cosmic rays, namely the atomic number $Z$ of rays with energies $E\gtrsim40~\mathrm{EeV}$, remains to date largely unknown. Some information on the composition can be inferred from the deflections that charged ultra-high-energy cosmic rays experience while they traverse intervening magnetic fields. Indeed, such deflections distort and suppress the original anisotropy in the cosmic ray arrival directions; thus, given a source model, a measure of the anisotropy is also a measurement of the deflections, which in turn informs us on the chemical composition. In this work, we show that, by quantifying ultra-high-energy cosmic ray anisotropies through the angular cross-correlation between cosmic rays and galaxies, we would be able to exclude iron fractions $f_{\rm Fe}\geq{\cal O}(10\%)$ assuming a fiducial hydrogen map at $2\,\sigma$ level, and even smaller fractions in the reverse case of hydrogen on an iron map, going well below $f_{\rm H}\approx10\%$ when we mask the Galactic Centre up to latitudes of $40^\circ$. This is an improvement of a factor of a few compared to our previous method, and is mostly ascribable to a new test statistics which is sensitive to each harmonic multipole individually. Our method can be applied to real data as an independent test of the recent claim that current cosmic-ray data can not be reproduced by any existing model of the Galactic magnetic field, as well as an additional handle to compare any realistic, competing, data-driven composition models.
Comments: 9 pages, 3 figures + appendix. Version matching publication at journal
Subjects: High Energy Astrophysical Phenomena (astro-ph.HE); Cosmology and Nongalactic Astrophysics (astro-ph.CO)
DOI: 10.1088/1475-7516/2024/03/058
Cite as: arXiv:2310.17699 [astro-ph.HE]
  (or arXiv:2310.17699v3 [astro-ph.HE] for this version)

Submission history

From: Konstantinos Tanidis [view email]
[v1] Thu, 26 Oct 2023 18:00:11 GMT (1164kb,D)
[v2] Mon, 30 Oct 2023 02:49:08 GMT (1164kb,D)
[v3] Mon, 22 Apr 2024 10:11:18 GMT (1168kb,D)

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