English

CRPropa 3.2 -- an advanced framework for high-energy particle propagation in extragalactic and galactic spaces

High Energy Astrophysical Phenomena 2022-09-13 v1 Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics

Abstract

The landscape of high- and ultra-high-energy astrophysics has changed in the last decade, largely due to the inflow of data collected by large-scale cosmic-ray, gamma-ray, and neutrino observatories. At the dawn of the multimessenger era, the interpretation of these observations within a consistent framework is important to elucidate the open questions in this field. CRPropa 3.2 is a Monte Carlo code for simulating the propagation of high-energy particles in the Universe. This version represents a major leap forward, significantly expanding the simulation framework and opening up the possibility for many more astrophysical applications. This includes, among others: efficient simulation of high-energy particles in diffusion-dominated domains, self-consistent and fast modelling of electromagnetic cascades with an extended set of channels for photon production, and studies of cosmic-ray diffusion tensors based on updated coherent and turbulent magnetic-field models. Furthermore, several technical updates and improvements are introduced with the new version, such as: enhanced interpolation, targeted emission of sources, and a new propagation algorithm (Boris push). The detailed description of all novel features is accompanied by a discussion and a selected number of example applications.

Keywords

Cite

@article{arxiv.2208.00107,
  title  = {CRPropa 3.2 -- an advanced framework for high-energy particle propagation in extragalactic and galactic spaces},
  author = {Rafael Alves Batista and Julia Becker Tjus and Julien Dörner and Andrej Dundovic and Björn Eichmann and Antonius Frie and Christopher Heiter and Mario R. Hoerbe and Karl-Heinz Kampert and Lukas Merten and Gero Müller and Patrick Reichherzer and Andrey Saveliev and Leander Schlegel and Günter Sigl and Arjen van Vliet and Tobias Winchen},
  journal= {arXiv preprint arXiv:2208.00107},
  year   = {2022}
}

Comments

32 pages, 9 figures