Finding high-redshift strong lenses in DES using convolutional neural networks. Issue 4 (25th January 2019)

• Record Type: Journal Article
• Authors: Jacobs, C; Collett, T; Glazebrook, K; McCarthy, C; Qin, A K; Abbott, T M C; Abdalla, F B; Annis, J; Avila, S; Bechtol, K; Bertin, E; Brooks, D; Buckley-Geer, E; Burke, D L; Carnero Rosell, A; Carrasco Kind, M; Carretero, J; da Costa, L N; Davis, C; De Vicente, J; Desai, S; Diehl, H T; Doel, P; Eifler, T F; Flaugher, B; Frieman, J; García-Bellido, J; Gaztanaga, E; Gerdes, D W; Goldstein, D A; Gruen, D; Gruendl, R A; Gschwend, J; Gutierrez, G; Hartley, W G; Hollowood, D L; Honscheid, K; Hoyle, B; James, D J; Kuehn, K; Kuropatkin, N; Lahav, O; Li, T S; Lima, M; Lin, H; Maia, M A G; Martini, P; Miller, C J; Miquel, R; Nord, B; Plazas, A A; Sanchez, E; Scarpine, V; Schubnell, M; Serrano, S; Sevilla-Noarbe, I; Smith, M; Soares-Santos, M; Sobreira, F; Suchyta, E; Swanson, M E C; Tarle, G; Vikram, V; Walker, A R; Zhang, Y; Zuntz, J;
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 484:Issue 4(2019)
• Page Start: 5330
• Page End: 5349
• Publication Date: 2019-01-25
• Subjects: gravitational lensing: strong -- methods: statistical; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stz272
• Languages: English
• ISSNs: 0035-8711

Abstract

Abstract: 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.