Finding high-redshift strong lenses in DES using convolutional neural networks
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 7,301 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 9,428 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.
Keywords
Cite
@article{arxiv.1811.03786,
title = {Finding high-redshift strong lenses in DES using convolutional neural networks},
author = {C. Jacobs and T. Collett and K. Glazebrook and C. McCarthy and A. K. Qin and T. M. C. Abbott and F. B. Abdalla and J. Annis and S. Avila and K. Bechtol and E. Bertin and D. Brooks and E. Buckley-Geer and D. L. Burke and A. Carnero Rosell and M. Carrasco Kind and J. Carretero and L. N. da Costa and C. Davis and J. De Vicente and S. Desai and H. T. Diehl and P. Doel and T. F. Eifler and B. Flaugher and J. Frieman and J. García- Bellido and E. Gaztanaga and D. W. Gerdes and D. A. Goldstein and D. Gruen and R. A. Gruendl and J. Gschwend and G. Gutierrez and W. G. Hartley and D. L. Hollowood and K. Honscheid and B. Hoyle and D. J. James and K. Kuehn and N. Kuropatkin and O. Lahav and T. S. Li and M. Lima and H. Lin and M. A. G. Maia and P. Martini and C. J. Miller and R. Miquel and B. Nord and A. A. Plazas and E. Sanchez and V. Scarpine and M. Schubnell and S. Serrano and I. Sevilla-Noarbe and M. Smith and M. Soares-Santos and F. Sobreira and E. Suchyta and M. E. C. Swanson and G. Tarle and V. Vikram and A. R. Walker and Y. Zhang and J. Zuntz},
journal= {arXiv preprint arXiv:1811.03786},
year = {2019}
}
Comments
Accepted for publication in MNRAS