Bayesian analysis of polarization measurements

TL;DR

This paper presents a Bayesian framework for analyzing polarization measurements with Gaussian errors, improving the accuracy of polarization degree and angle estimations across various signal-to-noise levels.

Contribution

It introduces a formal Bayesian approach tailored for polarization data, allowing customized prior selection and enhanced analysis at extreme signal-to-noise ratios.

Findings

Provides a comprehensive Bayesian analysis framework

Enhances measurement accuracy at low and high SNR

Allows for customized prior-based data analysis

Abstract

A detailed and formal account of polarization measurements using Bayesian analysis is given based on the assumption of gaussian error for the Stokes parameters. This analysis is crucial for the measurement of the polarization degree and angle at very low (and very high) signal-to-noise. The treatment serves as a framework for customized analysis of data based on a particular prior suited to the experiment.