A Robust Model for Flux Density Calculations of Radio Halos in Galaxy Clusters: Halo-FDCA

TL;DR

Halo-FDCA is an open-source Python tool that accurately models and estimates the total flux densities of radio halos in galaxy clusters, improving upon manual measurement methods.

Contribution

It introduces a flexible, automated fitting algorithm combining MCMC and theoretical models for more precise flux density estimation of radio halos.

Findings

Provides a robust, open-source Python package for flux density calculations.

Reduces biases and inaccuracies of manual measurement methods.

Suitable for large-scale studies of galaxy cluster radio halos.

Abstract

Here we present Halo-FDCA, a robust open source Python package for modeling and estimating total flux densities of radio (mini) halos in galaxy clusters. Radio halos are extended ( ~200 - 1500 kpc in size) synchrotron emitting sources found in galaxy clusters that trace the presence of cosmic rays and magnetic fields in the intracluster medium (ICM). These sources are centrally located and have a low surface brightness. Their exact origin is still unknown but they are likely related to cosmic rays being re-accelerated in-situ by merger or sloshing driven ICM turbulence. The presented algorithm combines the numerical power of the Markov Chain Monte Carlo routine and multiple theoretical models to estimate the total radio flux density of a radio halo from a radio image and its associated uncertainty. This method introduces a flexible analytic fitting procedure to replace existing simplistic manual measurements prone to biases and inaccuracies. It allows to easily determine the properties of the emission and is particularly suitable for future studies of large samples of clusters.