Multiband Probabilistic Cataloging: A Joint Fitting Approach to Point Source Detection and Deblending
Abstract
Probabilistic cataloging (PCAT) outperforms traditional cataloging methods on single-band optical data in crowded fields. We extend our work to multiple bands, achieving greater sensitivity (~0.4 mag) and greater speed (500×) compared to previous single-band results. We demonstrate the effectiveness of multiband PCAT on mock data, in terms of both recovering accurate posteriors in the catalog space and directly deblending sources. When applied to Sloan Digital Sky Survey (SDSS) observations of M2, taking Hubble Space Telescope data as truth, our joint fit on r- and i-band data goes ~0.4 mag deeper than single-band probabilistic cataloging and has a false discovery rate less than 20% for F606W ≤ 20. Compared to DAOPHOT, the two-band SDSS catalog fit goes nearly 1.5 mag deeper using the same data and maintains a lower false discovery rate down to F606W ~ 20.5. Given recent improvements in computational speed, multiband PCAT shows promise in application to large-scale surveys and is a plausible framework for joint analysis of multi-instrument observational data. https://github.com/RichardFeder/multiband_pcat.
Additional Information
© 2020 The American Astronomical Society. Received 2019 July 10; revised 2020 February 5; accepted 2020 February 9; published 2020 March 19. R.M.F. is supported by the California Institute of Technology and was also supported by the Harvard-Smithsonian Center for Astrophysics. S.K.N.P. acknowledges support from a Sir James Lougheed Award of Distinction, as well as the DIRAC Institute in the Department of Astronomy at the University of Washington. The DIRAC Institute is supported through generous gifts from the Charles and Lisa Simonyi Fund for Arts and Sciences and the Washington Research Foundation. T.D. acknowledges support from MIT's Kavli Institute as a Kavli postdoctoral fellow. We thank Aneta Siemiginowska, Vinay Kashyap, and Josh Speagle for useful comments throughout the course of this work. The computations in this paper were run on the Odyssey cluster supported by the FAS Division of Science, Research Computing Group at Harvard University. This research has made use of NASA's Astrophysics Data System. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS website is www.sdss.org. SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration, including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University. Software: Lion (Portillo et al. 2017), crowdsource (Schlafly et al. 2018), NumPy, Matplotlib, CBLAS, SciPy.Attached Files
Published - Feder_2020_AJ_159_163.pdf
Submitted - 1907.04929.pdf
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Additional details
- Eprint ID
- 100957
- Resolver ID
- CaltechAUTHORS:20200127-155716079
- Caltech
- Harvard-Smithsonian Center for Astrophysics
- DIRAC Institute
- University of Washington
- Charles and Lisa Simonyi Fund for Arts and Sciences
- Washington Research Foundation
- Massachusetts Institute of Technology (MIT)
- Alfred P. Sloan Foundation
- Department of Energy (DOE)
- Participating Institutions
- Created
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2020-01-28Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field