Subtraction of point sources from interferometric radio images through
  an algebraic forward modeling scheme
  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 of 10
arcsec and an average flux density error of 0.15%. This led to a dynamic range
increase of approximately 3 orders of magnitude. Since all the sources were
deconvolved jointly, the subtraction was not limited by source sidelobes but by
thermal noise. This technique is a promising deconvolution method for upcoming
radio arrays with a huge number of elements, and a candidate for the difficult
task of subtracting foreground sources from observations of the 21 cm neutral
Hydrogen signal from the epoch of reionization.
