Alternative algorithms for mitigating sparse-uv-sampling artifacts

Determine whether alternative radio-interferometric imaging and deconvolution algorithms can mitigate the impact of sparse uv sampling on the generation of spurious sources.

Background

The paper attributes the excess of spurious detections in high-resolution VLA surveys primarily to incomplete or sparse uv-plane sampling, which produces point-spread functions with strong sidelobes and consequently correlated image noise. The authors find that changing the tested imaging strategies does not significantly alter the spurious-source fraction, but they identify alternative imaging and deconvolution methods as a direction requiring further investigation.

Resolving this question is important for future deep continuum surveys with facilities such as the next-generation Very Large Array and the Square Kilometre Array, where high angular resolution combined with insufficiently dense uv coverage could otherwise increase the contamination of blind source catalogs by false detections.