Solving the Catalogue Cross-Match Problem in the Era of Gaia: The Effect of Unresolved Contaminant Objects on Photometric Catalogues

In this talk I will discuss the effect of blending from hidden, contaminant sources on the astrometry and photometry of catalogues such as LSST and WISE, using Gaia and its extremely high precision data to reveal this hidden problem which causes up to 50% of Gaia-WISE matches to be missed, and discuss how to overcome this problem with a Bayesian cross-match framework. I will introduce the generic "Astrometric Uncertainty Function", discuss the use of the photometric information to break false match degeneracies, and briefly touch on additional benefits this new cross-match method has, such as the natural inclusion of proper motion when cross-matching datasets with no proper motion information and statistics on the level of flux contamination sources in each catalogue suffers.