Finding high-redshift strong lenses in DES using convolutional neural networks
- Centre for Astrophysics & Supercomputing, Swinburne University of Technology, PO Box 218, Hawthorn, VIC 3122, Australia; ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Swinburne University of Technology, Hawthorn, VIC 3122, Australia
- Institute of Cosmology & Gravitation, University of Portsmouth, Portsmouth PO1 3FX, UK
- School of Software and Electrical Engineering, Swinburne University of Technology, PO Box 218, Hawthorn, VIC 3122, Australia
- Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, Casilla 603, 1700000 La Serena, Chile
- Department of Physics & Astronomy, University College London, Gower Street, London WC1E 6BT, UK; Department of Physics and Electronics, Rhodes University, PO Box 94, Grahamstown, 6140, South Africa
- Fermi National Accelerator Laboratory, PO Box 500, Batavia, IL 60510, USA
- LSST, 933 North Cherry Avenue, Tucson, AZ 85721, USA
- CNRS, UMR 7095, Institut d’Astrophysique de Paris, F-75014, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR 7095, Institut d’Astrophysique de Paris, F-75014, Paris, France
- Department of Physics & Astronomy, University College London, Gower Street, London WC1E 6BT, UK
- Kavli Institute for Particle Astrophysics & Cosmology, PO Box 2450, Stanford University, Stanford, CA 94305, USA; SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA
- Laboratório Interinstitucional de e-Astronomia – LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ – 20921-400, Brazil; Observatório Nacional, Rua Gal. José Cristino 77, Rio de Janeiro, RJ – 20921-400, Brazil
- Department of Astronomy, University of Illinois at Urbana-Champaign, 1002 W. Green Street, Urbana, IL 61801, USA; National Center for Supercomputing Applications, 1205 West Clark Str, Urbana, IL 61801, USA
- Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona), Spain
- Kavli Institute for Particle Astrophysics & Cosmology, PO Box 2450, Stanford University, Stanford, CA 94305, USA
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), 28040 Madrid, Spain
- Department of Physics, IIT Hyderabad, Kandi, Telangana 502285, India
- Department of Astronomy/Steward Observatory, 933 North Cherry Avenue, Tucson, AZ 85721-0065, USA; Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA
- Fermi National Accelerator Laboratory, PO Box 500, Batavia, IL 60510, USA; Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA
- Instituto de Fisica Teorica UAM/CSIC, Universidad Autonoma de Madrid, E-28049 Madrid, Spain
- Institut d’Estudis Espacials de Catalunya (IEEC), E-08193 Barcelona, Spain; Institute of Space Sciences (ICE, CSIC), Campus UAB, Carrer de Can Magrans, s/n, E-08193 Barcelona, Spain
- Department of Astronomy, University of Michigan, Ann Arbor, MI 48109, USA; Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Astronomy, University of California, Berkeley, 501 Campbell Hall, Berkeley, CA 94720, USA; Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- Department of Physics & Astronomy, University College London, Gower Street, London WC1E 6BT, UK; Department of Physics, ETH Zurich, Wolfgang-Pauli-Strasse 16, CH-8093 Zurich, Switzerland
- Santa Cruz Institute for Particle Physics, Santa Cruz, CA 95064, USA
- Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, OH 43210, USA; Department of Physics, The Ohio State University, Columbus, OH 43210, USA
- Max Planck Institute for Extraterrestrial Physics, Giessenbachstrasse, E-85748 Garching, Germany; Universitäts-Sternwarte, Fakultät für Physik, Ludwig-Maximilians Universität München, Scheinerstr. 1, D-81679 München, Germany
- Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138, USA
- Australian Astronomical Observatory, North Ryde, NSW 2113, Australia
- Laboratório Interinstitucional de e-Astronomia – LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ – 20921-400, Brazil; Departamento de Física Matemática, Instituto de Física, Universidade de São Paulo, CP 66318, São Paulo, SP, 05314-970, Brazil
- Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, OH 43210, USA; Department of Astronomy, The Ohio State University, Columbus, OH 43210, USA
- Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona), Spain; Institució Catalana de Recerca i Estudis Avançats, E-08010 Barcelona, Spain
- Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA
- Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
- School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ, UK
- Brandeis University, Physics Department, 415 South Street, Waltham, MA 02453, USA
- Laboratório Interinstitucional de e-Astronomia – LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ – 20921-400, Brazil; Instituto de Física Gleb Wataghin, Universidade Estadual de Campinas, Campinas, SP, 13083-859, Brazil
- Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- National Center for Supercomputing Applications, 1205 West Clark Str, Urbana, IL 61801, USA
- Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, USA
- Institute for Astronomy, University of Edinburgh, Edinburgh EH9 3HJ, UK
We search Dark Energy Survey (DES) Year 3 imaging data for galaxy-galaxy strong gravitational lenses using convolutional neural networks. We generate 250 000 simulated lenses at redshifts > 0.8 from which we create a data set for training the neural networks with realistic seeing, sky and shot noise. Using the simulations as a guide, we build a catalogue of 1.1 million DES sources with 1.8 < g - i < 5, 0.6 < g - r < 3, r_mag > 19, g_mag > 20, and i_mag > 18.2. We train two ensembles of neural networks on training sets consisting of simulated lenses, simulated non-lenses, and real sources. We use the neural networks to score images of each of the sources in our catalogue with a value from 0 to 1, and select those with scores greater than a chosen threshold for visual inspection, resulting in a candidate set of 7301 galaxies. During visual inspection, we rate 84 as 'probably' or 'definitely' lenses. Four of these are previously known lenses or lens candidates. We inspect a further 9428 candidates with a different score threshold, and identify four new candidates. We present 84 new strong lens candidates, selected after a few hours of visual inspection by astronomers. This catalogue contains a comparable number of high-redshift lenses to that predicted by simulations. Based on simulations, we estimate our sample to contain most discoverable lenses in this imaging and at this redshift range.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- Contributing Organization:
- DES Collaboration
- DOE Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1550886
- Journal Information:
- Monthly Notices of the Royal Astronomical Society, Vol. 484, Issue 4; ISSN 0035-8711
- Publisher:
- Royal Astronomical Society
- Country of Publication:
- United States
- Language:
- English
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