An Extended Catalog of Galaxy–Galaxy Strong Gravitational Lenses Discovered in DES Using Convolutional Neural Networks
AffiliationUniv Arizona, Steward Observ, Dept Astron
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PublisherIOP PUBLISHING LTD
CitationJacobs, C., Collett, T., Glazebrook, K., Buckley-Geer, E., Diehl, H. T., Lin, H., ... & Dial, P. (2019). An Extended Catalog of Galaxy–Galaxy Strong Gravitational Lenses Discovered in DES Using Convolutional Neural Networks. The Astrophysical Journal Supplement Series, 243(1), 17.
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AbstractWe search Dark Energy Survey (DES) Year 3 imaging for galaxy-galaxy strong gravitational lenses using convolutional neural networks, extending previous work with new training sets and covering a wider range of redshifts and colors. We train two neural networks using images of simulated lenses, then use them to score postage-stamp images of 7.9 million sources from DES chosen to have plausible lens colors based on simulations. We examine 1175 of the highest-scored candidates and identify 152 probable or definite lenses. Examining an additional 20,000 images with lower scores, we identify a further 247 probable or definite candidates. After including 86 candidates discovered in earlier searches using neural networks and 26 candidates discovered through visual inspection of blue-near-red objects in the DES catalog, we present a catalog of 511 lens candidates.
VersionFinal published version
SponsorsAustralian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D) [CE170100013]; Dennis Sciama Fellowship from the University of Portsmouth; U.S. Department of Energy; U.S. National Science Foundation; Ministry of Science and Education of Spain; Science and Technology Facilities Council of the United Kingdom; Higher Education Funding Council for England; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign; Kavli Institute of Cosmological Physics at the University of Chicago; Center for Cosmology and Astro-Particle Physics at the Ohio State University; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University; Financiadora de Estudos e Projetos; Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico; Ministerio da Ciencia, Tecnologia e Inovacao; Deutsche Forschungsgemeinschaft; Argonne National Laboratory; University of California at Santa Cruz; University of Cambridge; Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid; University of Chicago; University College London; DES-Brazil Consortium; University of Edinburgh; Eidgenossische Technische Hochschule (ETH) Zurich; Fermi National Accelerator Laboratory; University of Illinois at Urbana-Champaign; Institut de Ciencies de l'Espai (IEEC/CSIC); Institut de Fisica d'Altes Energies; Lawrence Berkeley National Laboratory; Ludwig-Maximilians Universitat Munchen; University of Michigan; National Optical Astronomy Observatory; University of Nottingham; Ohio State University; University of Pennsylvania; University of Portsmouth; SLAC National Accelerator Laboratory; Stanford University; University of Sussex; Texas AM University; OzDES Membership Consortium; National Science Foundation [AST-1138766, AST-1536171]; MINECO [AYA2015-71825, ESP2015-66861, FPA2015-68048, SEV2016-0588, SEV-2016-0597, MDM-2015-0509]; ERDF funds from the European Union; CERCA program of the Generalitat de Catalunya; European Research Council under the European Union [240672, 291329, 306478]; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO) [CE110001020]; Brazilian Instituto Nacional de Ciencia e Tecnologia (INCT) e-Universe (CNPq) [465376/2014-2]; U.S. Department of Energy, Office of Science, Office of High Energy Physics [DE-AC02-07CH11359]; National Aeronautics and Space Administration