Source finding in linear polarization for LOFAR, and SKA predecessor surveys, using Faraday moments

作者:Farnes J. S.*; Heald G.; Junklewitz H.; Mulcahy D. D.; Haverkorn M.; Van Eck C. L.; Riseley C. J.; Brentjens M.; Horellou C.; Vacca V.; Jones D. I.; Horneffer A.; Paladino R.
来源:Monthly Notices of the Royal Astronomical Society, 2018, 474(3): 3280-3296.
DOI:10.1093/mnras/stx2915

摘要

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 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 per cent at a signal to noise of 5. While the method has low reliability, rotation measure (RM) synthesis can be applied per candidate source to filter out instrumental and spurious detections. This combined strategy will result in a complete and reliable catalogue of polarized sources that includes the full sensitivity of the observational bandwidth. We find that the technique can reduce the number of pixels on which RM Synthesis needs to be performed by a factor of approximate to 1 x 10(5) for source distributions anticipated with modern radio telescopes. Through tests on LOFAR data, we find that the technique works effectively in the presence of diffuse emission. Extensions of this method are directly applicable to other upcoming radio surveys such as the POlarization Sky Survey of the Universe's Magnetism with the Australia Square Kilometre Array Pathfinder, and the SKA itself.

  • 出版日期2018-3
  • 单位CSIRO