naima: a Python package for inference of relativistic particle energy distributions from observed nonthermal spectra

TL;DR

Naima is an open-source Python package that models nonthermal emission from relativistic particles and fits observed spectra to infer particle distribution properties, aiding astrophysical source analysis.

Contribution

It introduces a comprehensive Python toolkit for modeling and fitting nonthermal spectra from relativistic particles, including user-defined distributions and MCMC fitting methods.

Findings

Successfully applied to a galactic nonthermal source

Provides flexible models for various radiative processes

Enables probabilistic inference of particle distributions

Abstract

The ultimate goal of the observation of nonthermal emission from astrophysical sources is to understand the underlying particle acceleration and evolution processes, and few tools are publicly available to infer the particle distribution properties from the observed photon spectra from X-ray to VHE gamma rays. Here I present naima, an open source Python package that provides models for nonthermal radiative emission from homogeneous distribution of relativistic electrons and protons. Contributions from synchrotron, inverse Compton, nonthermal bremsstrahlung, and neutral-pion decay can be computed for a series of functional shapes of the particle energy distributions, with the possibility of using user-defined particle distribution functions. In addition, naima provides a set of functions that allow to use these models to fit observed nonthermal spectra through an MCMC procedure, obtaining probability distribution functions for the particle distribution parameters. Here I present the models and methods available in naima and an example of their application to the understanding of a galactic nonthermal source. naima's documentation, including how to install the package, is available at http://naima.readthedocs.org.