Applying Bayesian Analysis to Radio Polarization Data

Astronomy and Astrophysics – Astronomy

Scientific paper

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Scientific paper

We apply Bayesian analysis to simulated polarization data. Our approach uses Markov Chain Monte Carlo and Nested Sampling algorithms to constrain source polarization properties, such as Faraday rotation of the polarization plane and depolarization. In particular, we investigate down to which signal-to-noise ratios rotation measures can be reliably recovered assuming instrument designs of the Square Kilometre Array and its pathfinders. Based on the Bayesian evidence, source spectral polarization models can be compared and an objective model selection is possible.

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