Stellar Streams as Probes of Dark Halo Mass and Morphology: A Bayesian Reconstruction

TL;DR

This paper introduces a Bayesian method to analyze stellar streams for inferring the shape and mass distribution of dark matter halos, even with limited observational data, by fitting stream projections and kinematic information.

Contribution

It presents a novel Bayesian approach using Parallel Tempering to constrain dark halo properties from stellar streams with minimal data.

Findings

Can constrain halo shape using only sky projections of streams.

Adding kinematic data improves mass and profile recovery.

Method successfully tested on simulated stellar streams.

Abstract

Tidal streams provide a powerful tool by means of which the matter distribution of the dark matter halos of their host galaxies can be studied. However, the analysis is not straightforward because streams do not delineate orbits, and for most streams, especially those in external galaxies, kinematic information is absent. We present a method wherein streams are fit with simple corrections made to possible orbits of the progenitor, using a Bayesian technique known as Parallel Tempering to efficiently explore the parameter space. We show that it is possible to constrain the shape of the host halo potential or its density distribution using only the projection of tidal streams on the sky, if the host halo is considered to be axisymmetric. By adding kinematic data or the circular velocity curve of the host to the fitting data, we are able to recover other parameters of the matter distribution such as its mass and profile. We test our method on several simulated low mass stellar streams and also explore the cases for which additional data are required.