Subtraction of point sources from interferometric radio images through an algebraic forward modeling scheme
G. Bernardi, D.A. Mitchell, S.M. Ord, L.J. Greenhill, B. Pindor, R.B., Wayth, J.S.B. Wyithe

TL;DR
This paper introduces an algebraic forward modeling method for subtracting point sources from interferometric radio images, significantly improving dynamic range and residual noise characteristics, especially useful for 21 cm cosmology.
Contribution
The paper presents a novel algebraic nonlinear minimization approach for point source subtraction that is effective with image-only data and scalable to large radio arrays.
Findings
Residual maps match thermal noise after subtraction
Recovered sources have ~10 arcsec position error
Achieved ~3 orders of magnitude increase in dynamic range
Abstract
We present a method for subtracting point sources from interferometric radio images via forward modeling of the instrument response and involving an algebraic nonlinear minimization. The method is applied to simulated maps of the Murchison Wide-field Array but is generally useful in cases where only image data are available. After source subtraction, the residual maps have no statistical difference to the expected thermal noise distribution at all angular scales, indicating high effectiveness in the subtraction. Simulations indicate that the errors in recovering the source parameters decrease with increasing signal-to-noise ratio, which is consistent with the theoretical measurement errors. In applying the technique to simulated snapshot observations with the Murchison Wide-field Array, we found that all 101 sources present in the simulation were recovered with an average position error…
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Taxonomy
TopicsGeophysics and Gravity Measurements · Radio Astronomy Observations and Technology · Synthetic Aperture Radar (SAR) Applications and Techniques
