Cosmic-ray propagation and production of secondary particles in the Galaxy

TL;DR

This thesis investigates cosmic-ray transport in the Galaxy using recent data, focusing on secondary particle production and addressing anomalies through improved modeling and uncertainty analysis.

Contribution

It introduces new analyses of cosmic-ray propagation, incorporates the upcoming DRAGON2 code, and emphasizes the importance of systematic uncertainties in interpreting anomalies.

Findings

Some propagation anomalies are resolved by considering systematic uncertainties.

Secondary particles like B, Be, Li, antiprotons, and gamma rays are used to test models.

Inclusion of cross section uncertainties improves model-data agreement.

Abstract

Cosmic rays are nowadays a crucial tool to study the astrophysics of extreme objects in the Universe, the cosmic environmental plasma (both Galactic and extra-galactic), the physics of nuclear interactions or the properties of elementary particles at very high energies and even cosmological problems such as the dark matter puzzle. In this thesis, the phenomenology on the transport of Galactic cosmic rays is studied in light of the most recent experimental data in the field and new analyses are presented in order to obtain better constraints. Throughout the thesis, secondary particles produced from collisions of cosmic rays with the interstellar gas, such as secondary cosmic ray nuclei (B, Be and Li), antiprotons and gamma rays, are treated in order to adjust and test our models and probe different scenarios, such as possible signatures of dark matter decay or annihilation. A preliminary version of the upcoming DRAGON2 code has been used to perform the propagation computations. With the increasing accuracy of CR data a number of anomalies have appear with respect to the standard paradigm of propagation of charged particles in the Galaxy. In this thesis, we demonstrate that some of these anomalies disappear by taking into account the systematic uncertainties involving these kind of analyses, specially cross sections uncertainties.