Source Finding in Linear Polarization for LOFAR, and SKA Predecessor Surveys, using Faraday Moments
J. S. Farnes, G. Heald, H. Junklewitz, D. D. Mulcahy, M. Haverkorn, C., L. Van Eck, C. J. Riseley, M. Brentjens, C. Horellou, V. Vacca, D. I. Jones,, A. Horneffer, R. Paladino

TL;DR
This paper introduces a novel 'Faraday Moments' method for detecting polarized radio sources in LOFAR and SKA precursor surveys, significantly reducing computational load while maintaining high completeness, and adaptable to future surveys.
Contribution
The paper presents a new source-finding strategy using statistical moments of polarization data, improving efficiency and applicability for large radio survey datasets.
Findings
Achieves 98.5% completeness at S/N of 5
Reduces RM Synthesis computations by a factor of 10^5
Effective in the presence of diffuse emission
Abstract
The optimal source-finding strategy for linear polarization data is an unsolved problem, with many inhibitive factors imposed by the technically-challenging nature of polarization observations. Such an algorithm is essential for Square Kilometre Array (SKA) pathfinder surveys, such as the Multifrequency Snapshot Sky Survey (MSSS) with the LOw Frequency ARray (LOFAR), as data volumes are significant enough to prohibit manual inspection. We present a new strategy of `Faraday Moments' for source-finding in linear polarization with LOFAR, using the moments of the frequency-dependent full-Stokes data (i.e. the mean, standard deviation, skewness, and excess kurtosis). Through simulations of the sky, we find that moments can identify polarized sources with a high completeness: 98.5% at a signal-to-noise of 5. While the method has low reliability, Rotation Measure (RM) Synthesis can be applied…
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