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Probabilistic cataloging (PCAT) outperforms traditional cataloging methods onsingle-band optical data in crowded fields (Portillo et al. 2017). We extendour work to multiple bands, achieving greater sensitivity ($\sim$ 0.4 mag) andgreater speed (500x) compared to previous single-band results. We demonstratethe effectiveness of multiband PCAT on mock data, both in terms of recoveringaccurate posteriors in the catalog space, and in directly deblending sources.When applied to Sloan Digital Sky Survey (SDSS) observations of M2, takingHubble Space Telescope data as truth, our joint fit on $r$ and $i$ band datagoes $\sim0.4$ mag deeper than single-band probabilistic cataloging and has afalse discovery rate less than 20\% for F606W$\leq 20$. Compared to DAOPHOT,the two-band SDSS catalog fit goes nearly 1.5 magnitudes deeper using the samedata, and maintains a lower false discovery rate down to F606W$\sim 20.5$.Given recent improvements in computational speed, multiband PCAT shows promisein application to large-scale surveys and is a plausible framework for jointanalysis of multi-instrument observational data.

Multiband Probabilistic Cataloging: A Joint Fitting Approach to Point Source Detection and Deblending