UCL Discovery Stage
UCL home » Library Services » Electronic resources » UCL Discovery Stage

An Extended Catalog of Galaxy-Galaxy Strong Gravitational Lenses Discovered in DES Using Convolutional Neural Networks

Jacobs, C; Collett, T; Glazebrook, K; Buckley-Geer, E; Diehl, HT; Lin, H; McCarthy, C; ... Zhang, Y; + view all (2019) An Extended Catalog of Galaxy-Galaxy Strong Gravitational Lenses Discovered in DES Using Convolutional Neural Networks. Astrophysical Journal Supplement , 243 (1) , Article 17. 10.3847/1538-4365/ab26b6. Green open access

[thumbnail of Jacobsetal_2019_VoR_ApJS_243_17.pdf]
Preview
Text
Jacobsetal_2019_VoR_ApJS_243_17.pdf - Published Version

Download (1MB) | Preview

Abstract

We 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.

Type: Article
Title: An Extended Catalog of Galaxy-Galaxy Strong Gravitational Lenses Discovered in DES Using Convolutional Neural Networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.3847/1538-4365/ab26b6
Publisher version: https://doi.org/10.3847/1538-4365/ab26b6
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: gravitational lensing: strong; methods: data analysis; methods: statistical; surveys
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10079395
Downloads since deposit
1,326Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item