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Astro Seminar

Towards Solving the Catalogue Cross-Match Problem

Speaker: Thomas Wilson (Exeter)
Date: Wednesday 1 June 2022
Time: 14:00
Venue: Zoom

One of the most fundamental processes in astronomy, the cross-matching of two photometric catalogues is the assignment of an object in one catalogue and one object from the second catalogue as pairs, i.e., different detections of the same physical source in the sky. This creates a composite catalogue greater than the sum of its parts, allowing for a host of scientific applications much more inaccessible without either set of data. Until recently, improvements in technology increased both the number of objects seen by a telescope, and the precision of the detected sources' error circles. New telescope surveys, such as the Vera C. Rubin Observatory's LSST, however, will be so crowded, even outside the Galactic plane, that standard cross-matching algorithms will fail. In this talk I will discuss the history of the catalogue cross-match, highlighting the algorithmic improvements used to overcome new challenges. In particular, I will introduce the Astrometric Uncertainty Function, the general belief in a source's true position given a measurement of its sky coordinates. This generalisation to the AUF will allow for two important extensions: the inclusion of a statistical description of offsets due to unknown proper motions, and a prescription for the perturbation of a source's measured position due to center-of-light tugs from faint, blended objects. Another important improvement to the identification of cross-catalogue pairings I will discuss is the use of the photometry of each source, using the fluxes of the detections to distinguish false matches from true identifications. Throughout the talk I will focus on two extreme catalogues to discuss these aspects of the cross-match problem: Gaia, with its very high angular resolution, and WISE, with its large point-spread function, subject to high levels of crowding. Finally, these efforts will be put into the context of our work as part of the LSST:UK consortium to develop a cross-match service that incorporates these developments to offer a robust object identification service.