Flaremodel: An open-source Python package for one-zone numerical modelling of synchrotron sources

TL;DR

Flaremodel is an open-source Python package designed for flexible, scalable one-zone numerical modeling of synchrotron sources, aiding astrophysical research near black holes and other energetic environments.

Contribution

It introduces a modular, high-performance Python tool with C-based core functions for simulating synchrotron sources, enhancing analytical models with numerical capabilities.

Findings

Provides a scalable, efficient modeling framework

Includes built-in source models and utility functions

Enables detailed exploration of complex synchrotron sources

Abstract

Synchrotron processes, the radiative processes associated with the interaction of energetic charged particles with magnetic field, are of interest in many areas in astronomy, from the interstellar medium to extreme environments near compact objects. Consequently, observations of synchrotron sources carry information on the physical properties of the sources themselves and those of their close vicinity. In recent years, novel observations of such sources with multi-wavelength collaborations reveal complex features and peculiarities, especially near black holes. Exploring the nature of these sources in more detail necessitates numerical tools complementary to analytical one-zone modelling efforts. In this paper, we introduce an open-source Python package tailored to this purpose, flaremodel. The core of the code consists of low-level utility functions to describe physical processes relevant to synchrotron sources, which are written in C for performance and parallelised with OpenMP for scalability. The Python interface provides access to these functions and built-in source models are provided as a guidance. At the same time, the modular design of the code and the generic nature of these functions enable users to build a variety of source models applicable to many astrophysical synchrotron sources. We describe our methodology and the structure of our code along with selected examples demonstrating capabilities and options for future modelling efforts.