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.

{"references": ["Sutherland & Saunders (1992): On the likelihood ratio for source identification.", "Wright et al. (2010): The Wide-field Infrared Survey Explorer (WISE): Mission Description and Initial On-orbit Performance", "Ricker et al. (2015): Transiting Exoplanet Survey Satellite (TESS)", "Wilson & Naylor (2017): The effect of unresolved contaminant stars on the cross-matching of photometric catalogues", "Wilson & Naylor (2018): Improving catalogue matching by supplementing astrometry with additional photometric information", "Wilson & Naylor (2018): A contaminant-free catalogue of Gaia DR2-WISE Galactic plane matches: including the effects of crowding in the cross-matching of photometric catalogues"]}