# A new method to suppress the bias in polarized intensity

## TL;DR

This paper introduces a novel bias suppression method for polarized intensity maps that accurately estimates the true signal even in noisy environments, improving analysis of faint sources and interstellar turbulence.

## Contribution

A new bias correction technique using a modified median filter to estimate polarization angles, applicable to Gaussian and non-Gaussian noise, enhancing the accuracy of polarized intensity measurements.

## Key findings

- Accurately recovers true polarized intensity in noisy data.
- Works effectively with Gaussian and non-Gaussian noise distributions.
- Produces smoother maps of low-intensity features like depolarisation canals.

## Abstract

Computing polarised intensities from noisy data in Stokes U and Q suffers from a positive bias that should be suppressed. To develop a correction method that, when applied to maps, should provide a distribution of polarised intensity that closely follows the signal from the source. We propose a new method to suppress the bias by estimating the polarisation angle of the source signal in a noisy environment with help of a modified median filter. We then determine the polarised intensity, including the noise, by projection of the observed values of Stokes U and Q onto the direction of this polarisation angle. We show that our new method represents the true signal very well. If the noise distribution in the maps of U and Q is Gaussian, then in the corrected map of polarised intensity it is also Gaussian. Smoothing to larger Gaussian beamsizes, to improve the signal-to-noise ratio, can be done directly with our method in the map of the polarised intensity. Our method also works in case of non-Gaussian noise distributions. The maps of the corrected polarised intensities and polarisation angles are reliable even in regions with weak signals and provide integrated flux densities and degrees of polarisation without the cumulative effect of the bias, which especially affects faint sources. Features at low intensity levels like 'depolarisation canals' are smoother than in the maps using the previous methods, which has broader implications, for example on the interpretation of interstellar turbulence.