diffSph: a Python tool to compute diffuse signals from dwarf spheroidal galaxies

Abstract

So far no diffuse emissions in dwarf spheroidal satellites of the Milky Way have ever been observed. Given that dwarf galaxies are predominantly composed of Dark Matter, the discovery of these signals could offer valuable insights into understanding the nature of Dark Matter. We present “diffSph”, a Python tool which in its present version provides fast predictions of such diffuse signals in radio frequencies. It also features a very comprehensive module for the computation of “J” and “D” factors that are relevant for indirect Dark Matter detection using gamma rays. Routines are coupled to parton-shower algorithms and Dark Matter halo mass functions from state-of-the-art kinematic fits. This code is also useful for testing generic hypotheses (not necessarily associated with any Dark Matter candidate) about the cosmic-ray electron/positron sources in the dwarf galaxies. The diffSph tool has already been employed in searches for diffuse signals from dwarf spheroidal galaxies using the LOw Frequency ARray (LOFAR).