Bayesian Source Discrimination in Radio Interferometry

Abstract

Methods currently in use for locating and characterising sources in radio interferometry maps are designed for processing images, and require interferometric maps to be preprocessed so as to resemble conventional images. We demonstrate a Bayesian code - BaSC - that takes into account the interferometric visibility data despite working with more computationally manageable image domain data products. This method is better able to discriminate nearby sources than the commonly used SExtractor, and has potential even in more complicated cases. We also demonstrate the correctness of the Bayesian resolving formula for simulated data, and its implications for source discrimination at distances below the full width half maximum of the restoring beam.