Wednesday

As part of the LSST:UK consortium, supporting Rubin Observatory science with LSST, we are implementing a cross-match service. This service will provide information on objects detected in both LSST data releases and external datasets, such as Gaia or WISE, to enable the combined photometric catalogue to be used to answer a wide range of open research questions. In this talk I will outline the service, highlighting the novel aspects of the matching algorithm, crucial for the correct identification of sources subject to high levels of crowding, like those LSST will suffer with its incredible completeness limit.

In particular I will discuss our work implementing a prescription for the effect of blended objects, which perturb the center-of-light of the brighter source, potentially leading to otherwise unexplainable separations between two genuine detections of one physical sky object. I will also touch upon our methodology for the inclusion of the brightness of the objects being matched, which allows for the rejection of false matches through unlikely colours of potential counterpart pairings. I will then discuss the expected interaction DAC users will have with the matches, the additional information we will provide along with the most probable counterpart correspondence between pairs of sources, and the scientific uses for these extra pieces of information. Finally, I will briefly discuss some potential extensions to the service -- chiefly the inclusion of a model for unknown proper motions -- and highlight a few key areas of Early Rubin Science for which we think this service might be of great use.