A Bayesian Framework for UHECR Source Association and Parameter Inference

Fuente: arXiv
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Autores principales: Watanabe, Keito, Fedynitch, Anatoli, Capel, Francesca, Sagawa, Hiroyuki
Formato: Preprint
Publicado: 2025
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author Watanabe, Keito
Fedynitch, Anatoli
Capel, Francesca
Sagawa, Hiroyuki
author_facet Watanabe, Keito
Fedynitch, Anatoli
Capel, Francesca
Sagawa, Hiroyuki
contents The identification of potential sources of ultra-high-energy cosmic rays (UHECRs) remains challenging due to magnetic deflections and propagation losses, which are particularly strong for nuclei. In previous iterations of this work, we proposed an approach for UHECR astronomy based on Bayesian inference through explicit modelling of propagation and magnetic deflection effects. The event-by-event mass information is expected to provide tighter constraints on these parameters and to help identify unknown sources. However, the measurements of the average mass through observations from the surface detectors at the Pierre Auger Observatory already indicate that the UHECR masses are well represented through its statistical average. In this contribution, we present our framework which uses energy and mass moments of $\ln A$ to infer the source parameters of UHECRs, including the mass composition at the source. We demonstrate the performance of our model using simulated datasets based on the Pierre Auger Observatory and Telescope Array Project. Our model can be readily applied to currently available data, and we discuss the implications of our results for UHECR source identification.
format Preprint
id arxiv_https___arxiv_org_abs_2507_07856
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Bayesian Framework for UHECR Source Association and Parameter Inference
Watanabe, Keito
Fedynitch, Anatoli
Capel, Francesca
Sagawa, Hiroyuki
High Energy Astrophysical Phenomena
Instrumentation and Methods for Astrophysics
The identification of potential sources of ultra-high-energy cosmic rays (UHECRs) remains challenging due to magnetic deflections and propagation losses, which are particularly strong for nuclei. In previous iterations of this work, we proposed an approach for UHECR astronomy based on Bayesian inference through explicit modelling of propagation and magnetic deflection effects. The event-by-event mass information is expected to provide tighter constraints on these parameters and to help identify unknown sources. However, the measurements of the average mass through observations from the surface detectors at the Pierre Auger Observatory already indicate that the UHECR masses are well represented through its statistical average. In this contribution, we present our framework which uses energy and mass moments of $\ln A$ to infer the source parameters of UHECRs, including the mass composition at the source. We demonstrate the performance of our model using simulated datasets based on the Pierre Auger Observatory and Telescope Array Project. Our model can be readily applied to currently available data, and we discuss the implications of our results for UHECR source identification.
title A Bayesian Framework for UHECR Source Association and Parameter Inference
topic High Energy Astrophysical Phenomena
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2507.07856