2015MNRAS.451.1299F

Cross-matching catalogues at different wavelengths is a difficult problem in astronomy, especially when the objects are not point-like. At radio wavelengths, an object can have several components corresponding, for example, to a core and lobes. Considering not all radio detections correspond to visible or infrared sources, matching these catalogues can be challenging. Traditionally, this is done by eye for better quality, which does not scale to the large data volumes expected from the next-generation of radio telescopes. We present a novel automated procedure, using Bayesian hypothesis testing, to achieve reliable associations by explicit modelling of a particular class of radio-source morphology. The new algorithm not only assesses the likelihood of an association between data at two different wavelengths, but also tries to assess whether different radio sources are physically associated, are double-lobed radio galaxies, or just distinct nearby objects. Application to the Spitzer Wide-Area Infrared Extragalactic and Australia Telescope Large Area Survey CDF-S catalogues shows that this method performs well without human intervention.