Investigating the CREDIT history of supernova remnants as cosmic-ray sources
Anton Stall, Chun Khai Loo, Philipp Mertsch

TL;DR
This paper proposes a spectral signature called CREDIT that can identify individual supernova remnants as sources of Galactic cosmic rays by detecting energy-dependent features in cosmic-ray fluxes.
Contribution
It introduces a novel spectral signature based on energy-dependent escape from SNRs and demonstrates its detectability using Monte Carlo simulations and machine learning.
Findings
Predicted flux enhancements in narrow rigidity intervals for young, nearby SNRs.
A trained decision tree can distinguish between smooth and stochastic source distributions.
The CREDIT scenario offers a new approach for identifying SNRs as cosmic-ray sources.
Abstract
Supernova remnants (SNRs) have long been suspected to be the primary sources of Galactic cosmic rays. Over the past decades, great strides have been made in the modelling of particle acceleration, magnetic field amplification, and escape from SNRs. Yet, while many SNRs have been observed in non-thermal emission in radio, X-rays, and gamma-rays, there is no evidence for any individual object contributing to the locally observed flux. Here, we propose a particular spectral signature from individual remnants that is due to the energy-dependent escape from SNRs. For young and nearby sources, we predict fluxes enhanced by tens of percent in narrow rigidity intervals; given the percent-level flux uncertainties of contemporary cosmic-ray data, such features should be readily detectable. We model the spatial and temporal distribution of sources and the resulting distribution of fluxes with a…
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Taxonomy
TopicsAstrophysics and Cosmic Phenomena · Earthquake Detection and Analysis · Radiation Detection and Scintillator Technologies
