[Paper Review] The GALPROP Cosmic-ray Propagation and Non-thermal Emissions Framework: Release v57

T. A. Porter, G. Jóhannesson+1 more|arXiv (Cornell University)|Dec 23, 2021

Dark Matter and Cosmic PhenomenaPhysics and Astronomy155 references77 citations

TL;DR

This paper presents GALPROP v57, a major update to the state-of-the-art cosmic-ray propagation and non-thermal emission framework, enabling self-consistent, time-dependent 3D modeling of cosmic rays and their emissions across 18 orders of magnitude in energy. The release includes updated nuclear cross sections, enhanced interstellar medium modeling, and new capabilities for high-precision interpretation of multiwavelength data from space- and ground-based observatories, particularly in the very high-energy (VHE; >100 GeV) range.

ABSTRACT

The past decade has brought impressive advances in the astrophysics of cosmic rays (CRs) and multiwavelength astronomy, thanks to the new instrumentation launched into space and built on the ground. Modern technologies employed by those instruments provide measurements with unmatched precision, enabling searches for subtle signatures of dark matter (DM) and new physics. Understanding the astrophysical backgrounds to better precision than the observed data is vital in moving to this new territory. The state-of-the-art CR propagation code called GALPROP is designed to address exactly this challenge. Having 25 years of development behind it, the GALPROP framework has become a de-facto standard in the astrophysics of CRs, diffuse photon emissions (radio- to gamma-rays), and searches for new physics. GALPROP uses information from astronomy, particle physics, and nuclear physics to predict CRs and their associated emissions self-consistently, providing a unifying modelling framework. The range of its physical validity covers 18 orders of magnitude in energy, from sub-keV to PeV energies for particles and from micro-eV to PeV energies for photons. The framework and the datasets are public and are extensively used by many experimental collaborations and by thousands of individual researchers worldwide for interpretation of their data and for making predictions. This paper details the latest release of the GALPROP framework and updated cross sections, further developments of its initially auxiliary datasets for models of the interstellar medium that grew into independent studies of the Galactic structure -- distributions of gas, dust, radiation and magnetic fields -- as well as the extension of its modelling capabilities. Example applications included with the distribution illustrating usage of the new features are also described.

Motivation & Objective

• To enable self-consistent, time-dependent 3D modeling of cosmic-ray propagation and non-thermal emissions across the Milky Way.
• To improve the precision of cosmic-ray propagation models by incorporating updated nuclear cross sections and astrophysical datasets.
• To support the interpretation of high-precision data from modern space- and ground-based observatories, including CALET, DAMPE, HAWC, and LHASSO.
• To provide a public, extensible framework for modeling cosmic rays, diffuse emissions, and searches for new physics across 18 orders of magnitude in energy.
• To extend the GALPROP framework into a comprehensive tool for interstellar medium structure, including gas, dust, radiation, and magnetic fields.

Proposed method

• The GALPROP code solves a system of ~90 time-dependent transport equations in 3D or 4D (spatial + energy variables), including convection, diffusion, energy losses, and nuclear fragmentation.
• It uses a flexible source model composition scheme allowing custom spatial distributions, injection spectra, and isotopic abundances for multiple CR source populations (e.g., SNRs, PWNe).
• The framework incorporates updated nuclear cross sections for key reactions, including 3He(p,ppX)d and pp→π++d, using detailed balance and empirical fits to experimental data.
• It models the interstellar radiation field (ISRF), magnetic fields, and gas/dust distributions self-consistently, with datasets now treated as independent astrophysical studies.
• The code supports variable diffusion coefficients dependent on position and rigidity, with options for Kolmogorov or Iroshnikov–Kraichnan turbulence spectra.
• A web-based interface (WEBRUN) enables remote execution, and the full framework and datasets are publicly available.

Experimental results

Research questions

• RQ1 How can cosmic-ray propagation and non-thermal emission be modeled self-consistently across 18 orders of magnitude in energy, from sub-keV to PeV?
• RQ2 What improvements in nuclear cross sections are required to accurately model secondary particle production in cosmic-ray interactions?
• RQ3 How can time-dependent, 3D modeling of cosmic-ray propagation be made computationally tractable for modern high-energy data?
• RQ4 What role do spatially varying diffusion coefficients and magnetic field distributions play in shaping cosmic-ray and emission profiles?
• RQ5 How can the GALPROP framework be extended to model the interstellar medium’s structure—including gas, dust, radiation, and magnetic fields—beyond its original scope?

Key findings

• GALPROP v57 enables time-dependent, 3D modeling of cosmic-ray propagation and associated non-thermal emissions, crucial for interpreting new VHE data from CALET, DAMPE, HAWC, and LHASSO.
• The framework now includes updated cross sections for key reactions such as 3He(p,ppX)d and pp→π++d, with empirical fits to experimental data across 288–4000 MeV proton kinetic energy.
• The cross section for pp→π++d is modeled with a power-law tail above 970 MeV, with δ = 2.9 and a normalization q = 0.4675, matching high-energy data.
• The formalism for deuteron production in pp collisions is validated using detailed balance and CMS kinematics, with a maximum cross section at Tp ≈ 560 MeV.
• Cross sections for 3He, 3H, and 2H production in p+A and α+A reactions are scaled using A-dependent factors and energy-dependent functions, with F(Ek,A) accounting for energy and mass dependence.
• The interstellar medium datasets—gas, dust, radiation, and magnetic fields—have evolved into independent astrophysical studies, enhancing the framework’s physical realism and predictive power.