@article{d28dbef7437a4e278d7fd399fd3ee36e,
title = "Approximate inference for constructing astronomical catalogs from images",
abstract = "We present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets. Each pixel intensity is treated as a random variable with parameters that depend on the latent properties of stars and galaxies. These latent properties are themselves modeled as random. We compare two procedures for posterior inference. One procedure is based on Markov chain Monte Carlo (MCMC) while the other is based on variational inference (VI). The MCMC procedure excels at quantifying uncertainty, while the VI procedure is 1000 times faster. On a supercomputer, the VI procedure efficiently uses 665,000 CPU cores to construct an astronomical catalog from 50 terabytes of images in 14.6 minutes, demonstrating the scaling characteristics necessary to construct catalogs for upcoming astronomical surveys.",
keywords = "Astronomy, Graphical model, High performance computing, MCMC, Variational inference",
author = "{The Voleon Group} and Jeffrey Regier and Miller, {Andrew C.} and David Schlegel and Adams, {Ryan P.} and McAuliffe, {Jon D.} and Prabhat",
note = "Funding Information: 1The National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy, funded our research through Contract No. DE-AC02-05CH11231. 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 acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org. Funding Information: 1 The National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy, funded our research through Contract No. DE-AC02-05CH11231. 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 acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org. Publisher Copyright: {\textcopyright} Institute of Mathematical Statistics, 2019.",
year = "2019",
month = sep,
doi = "10.1214/19-AOAS1258",
language = "English (US)",
volume = "13",
pages = "1884--1926",
journal = "Annals of Applied Statistics",
issn = "1932-6157",
publisher = "Institute of Mathematical Statistics",
number = "3",
}