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

C. Jacobs; T. Collett; K. Glazebrook; E. Buckley-Geer; H. T. Diehl; H. Lin; C. McCarthy; A. K. Qin; C. Odden; M. Caso Escudero; P. Dial; V. J. Yung; S. Gaitsch; A. Pellico; K. A. Lindgren; T. M.C. Abbott; J. Annis; S. Avila; D. Brooks; D. L. Burke; A. Carnero Rosell; M. Carrasco Kind; J. Carretero; L. N.Da Costa; J. De Vicente; P. Fosalba; J. Frieman; J. García-Bellido; E. Gaztanaga; D. A. Goldstein; D. Gruen; R. A. Gruendl; J. Gschwend; D. L. Hollowood; K. Honscheid; B. Hoyle; D. J. James; E. Krause; N. Kuropatkin; O. Lahav; M. Lima; M. A.G. Maia; J. L. Marshall; R. Miquel; A. A. Plazas; A. Roodman; E. Sanchez; V. Scarpine; S. Serrano; I. Sevilla-Noarbe; M. Smith; F. Sobreira; E. Suchyta; M. E.C. Swanson; G. Tarle; V. Vikram; A. R. Walker; Y. Zhang

doi:10.3847/1538-4365/ab26b6

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

C. Jacobs
, T. Collett
, K. Glazebrook
, E. Buckley-Geer
, H. T. Diehl
, H. Lin
, C. McCarthy
, A. K. Qin
, C. Odden
, M. Caso Escudero
, P. Dial
, V. J. Yung
, S. Gaitsch
, A. Pellico
, K. A. Lindgren
, T. M.C. Abbott
, J. Annis
, S. Avila
, D. Brooks
, D. L. Burke

A. Carnero Rosell, M. Carrasco Kind, J. Carretero, L. N.Da Costa, J. De Vicente, P. Fosalba, J. Frieman, J. García-Bellido, E. Gaztanaga, D. A. Goldstein, D. Gruen, R. A. Gruendl, J. Gschwend, D. L. Hollowood, K. Honscheid, B. Hoyle, D. J. James, E. Krause, N. Kuropatkin, O. Lahav, M. Lima, M. A.G. Maia, J. L. Marshall, R. Miquel, A. A. Plazas, A. Roodman, E. Sanchez, V. Scarpine, S. Serrano, I. Sevilla-Noarbe, M. Smith, F. Sobreira, E. Suchyta, M. E.C. Swanson, G. Tarle, V. Vikram, A. R. Walker, Y. Zhang

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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.

Original language	English
Article number	17
Journal	Astrophysical Journal, Supplement Series
Volume	243
Issue number	1
DOIs	https://doi.org/10.3847/1538-4365/ab26b6
State	Published - 2019

Keywords

gravitational lensing: strong
methods: data analysis
methods: statistical
surveys

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10.3847/1538-4365/ab26b6

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Jacobs, C., Collett, T., Glazebrook, K., Buckley-Geer, E., Diehl, H. T., Lin, H., McCarthy, C., Qin, A. K., Odden, C., Escudero, M. C., Dial, P., Yung, V. J., Gaitsch, S., Pellico, A., Lindgren, K. A., Abbott, T. M. C., Annis, J., Avila, S., Brooks, D., ... Zhang, Y. (2019). An Extended Catalog of Galaxy-Galaxy Strong Gravitational Lenses Discovered in des Using Convolutional Neural Networks. Astrophysical Journal, Supplement Series, 243(1), Article 17. https://doi.org/10.3847/1538-4365/ab26b6

@article{3c95ab75c5a84a61848e0500671a6867,

title = "An Extended Catalog of Galaxy-Galaxy Strong Gravitational Lenses Discovered in des Using Convolutional Neural Networks",

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.",

keywords = "gravitational lensing: strong, methods: data analysis, methods: statistical, surveys",

author = "C. Jacobs and T. Collett and K. Glazebrook and E. Buckley-Geer and Diehl, \{H. T.\} and H. Lin and C. McCarthy and Qin, \{A. K.\} and C. Odden and Escudero, \{M. Caso\} and P. Dial and Yung, \{V. J.\} and S. Gaitsch and A. Pellico and Lindgren, \{K. A.\} and Abbott, \{T. M.C.\} and J. Annis and S. Avila and D. Brooks and Burke, \{D. L.\} and Rosell, \{A. Carnero\} and Kind, \{M. Carrasco\} and J. Carretero and Costa, \{L. N.Da\} and Vicente, \{J. De\} and P. Fosalba and J. Frieman and J. Garc{\'i}a-Bellido and E. Gaztanaga and Goldstein, \{D. A.\} and D. Gruen and Gruendl, \{R. A.\} and J. Gschwend and Hollowood, \{D. L.\} and K. Honscheid and B. Hoyle and James, \{D. J.\} and E. Krause and N. Kuropatkin and O. Lahav and M. Lima and Maia, \{M. A.G.\} and Marshall, \{J. L.\} and R. Miquel and Plazas, \{A. A.\} and A. Roodman and E. Sanchez and V. Scarpine and S. Serrano and I. Sevilla-Noarbe and M. Smith and F. Sobreira and E. Suchyta and Swanson, \{M. E.C.\} and G. Tarle and V. Vikram and Walker, \{A. R.\} and Y. Zhang",

year = "2019",

doi = "10.3847/1538-4365/ab26b6",

language = "English",

volume = "243",

journal = "Astrophysical Journal, Supplement Series",

issn = "0067-0049",

publisher = "American Astronomical Society",

number = "1",

}

Jacobs, C, Collett, T, Glazebrook, K, Buckley-Geer, E, Diehl, HT, Lin, H, McCarthy, C, Qin, AK, Odden, C, Escudero, MC, Dial, P, Yung, VJ, Gaitsch, S, Pellico, A, Lindgren, KA, Abbott, TMC, Annis, J, Avila, S, Brooks, D, Burke, DL, Rosell, AC, Kind, MC, Carretero, J, Costa, LND, Vicente, JD, Fosalba, P, Frieman, J, García-Bellido, J, Gaztanaga, E, Goldstein, DA, Gruen, D, Gruendl, RA, Gschwend, J, Hollowood, DL, Honscheid, K, Hoyle, B, James, DJ, Krause, E, Kuropatkin, N, Lahav, O, Lima, M, Maia, MAG, Marshall, JL, Miquel, R, Plazas, AA, Roodman, A, Sanchez, E, Scarpine, V, Serrano, S, Sevilla-Noarbe, I, Smith, M, Sobreira, F, Suchyta, E, Swanson, MEC, Tarle, G, Vikram, V, Walker, AR & Zhang, Y 2019, 'An Extended Catalog of Galaxy-Galaxy Strong Gravitational Lenses Discovered in des Using Convolutional Neural Networks', Astrophysical Journal, Supplement Series, vol. 243, no. 1, 17. https://doi.org/10.3847/1538-4365/ab26b6

TY - JOUR

T1 - An Extended Catalog of Galaxy-Galaxy Strong Gravitational Lenses Discovered in des Using Convolutional Neural Networks

AU - Jacobs, C.

AU - Collett, T.

AU - Glazebrook, K.

AU - Buckley-Geer, E.

AU - Diehl, H. T.

AU - Lin, H.

AU - McCarthy, C.

AU - Qin, A. K.

AU - Odden, C.

AU - Escudero, M. Caso

AU - Dial, P.

AU - Yung, V. J.

AU - Gaitsch, S.

AU - Pellico, A.

AU - Lindgren, K. A.

AU - Abbott, T. M.C.

AU - Annis, J.

AU - Avila, S.

AU - Brooks, D.

AU - Burke, D. L.

AU - Rosell, A. Carnero

AU - Kind, M. Carrasco

AU - Carretero, J.

AU - Costa, L. N.Da

AU - Vicente, J. De

AU - Fosalba, P.

AU - Frieman, J.

AU - García-Bellido, J.

AU - Gaztanaga, E.

AU - Goldstein, D. A.

AU - Gruen, D.

AU - Gruendl, R. A.

AU - Gschwend, J.

AU - Hollowood, D. L.

AU - Honscheid, K.

AU - Hoyle, B.

AU - James, D. J.

AU - Krause, E.

AU - Kuropatkin, N.

AU - Lahav, O.

AU - Lima, M.

AU - Maia, M. A.G.

AU - Marshall, J. L.

AU - Miquel, R.

AU - Plazas, A. A.

AU - Roodman, A.

AU - Sanchez, E.

AU - Scarpine, V.

AU - Serrano, S.

AU - Sevilla-Noarbe, I.

AU - Smith, M.

AU - Sobreira, F.

AU - Suchyta, E.

AU - Swanson, M. E.C.

AU - Tarle, G.

AU - Vikram, V.

AU - Walker, A. R.

AU - Zhang, Y.

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - gravitational lensing: strong

KW - methods: data analysis

KW - methods: statistical

KW - surveys

UR - https://www.scopus.com/pages/publications/85071163691

U2 - 10.3847/1538-4365/ab26b6

DO - 10.3847/1538-4365/ab26b6

M3 - Article

AN - SCOPUS:85071163691

SN - 0067-0049

VL - 243

JO - Astrophysical Journal, Supplement Series

JF - Astrophysical Journal, Supplement Series

IS - 1

M1 - 17

ER -

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

Abstract

Keywords

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