Probabilistic Cross-Identification of Astronomical Sources

Abstract

We present a general probabilistic formalism for cross-identifying astronomical point sources in multiple observations. Our Bayesian approach, symmetric in all observations, is the foundation of a unified framework for object matching, where not only spatial information, but physical properties, such as colors, redshift and luminosity, can also be considered in a natural way. We provide a practical recipe to implement an efficient recursive algorithm to evaluate the Bayes factor over a set of catalogs with known circular errors in positions. This new methodology is crucial for studies leveraging the synergy of today's multi-wavelength observations and to enter the time-domain science of the upcoming survey telescopes.

Accepted for publication in the Astrophysical Journal, 8 pages, 1 figure, emulateapj w/ apjfonts

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