Dark matter in disk galaxies I: a Markov Chain Monte Carlo method and application to DDO 154
Peter R Hague, Mark I Wilkinson

TL;DR
This paper introduces a new MCMC-based method to robustly constrain dark matter halo profiles in disk galaxies, effectively handling model degeneracies and applying it to DDO 154 to validate previous findings.
Contribution
The paper develops a comprehensive MCMC approach that explores a wide range of dark matter profiles, improving robustness over previous methods and identifying cases where data are insufficient.
Findings
Reliable estimates of halo density profiles can be obtained from current data.
The logarithmic slope at the innermost radius is well constrained in LSB galaxies.
The method confirms earlier estimates for DDO 154's halo slope.
Abstract
We present a new method to constrain the dark matter halo density profiles of disk galaxies. Our algorithm employs a Markov Chain Monte Carlo (MCMC) approach to explore the parameter space of a general family of dark matter profiles. We improve upon previous analyses by considering a wider range of halo profiles and by explicitly identifying cases in which the data are insufficient to break the degeneracies between the model parameters. We demonstrate the robustness of our algorithm using artificial data sets and show that reliable estimates of the halo density profile can be obtained from data of comparable quality to those currently available for low surface brightness (LSB) galaxies. We present our results in terms of physical quantities which are constrained by the data, and find that the logarithmic slope of the halo density profile at the radius of the innermost data point of a…
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