Solving the Catalogue Cross-Match Problem in the Era of LSST: The Effect of Unresolved Contaminant Objects and Proper Motions on Photometric Catalogues

Traditional photometric catalogue matching will fail for Rubin Obs. LSST, as typical 2” error circles will contain up to 10 random objects. Bayesian cross-matching techniques which include the astrometric uncertainty of the observations ultimately assume that the Astrometric Uncertainty Function of the sources is Gaussian, which will not apply to LSST. The extreme source densities and significant number of objects with no known proper motion mean that systematic effects, not noise-based scatter, dominant the separations of objects between LSST and other surveys. As part of the LSST:UK consortium we have developed and are implementing methods to handle these effects, vital to being able to trust any composite dataset created, and will be producing robust cross-matches between LSST and a wide range of other catalogues.