J/MNRAS/484/5330 High-redshift strong lens candidates from DES (Jacobs+, 2019)
Finding high-redshift strong lenses in DES using convolutional neural networks.
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., Garcia-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.,
(The DES Collaboration)
<Mon. Not. R. Astron. Soc., 484, 5330-5349 (2019)>
=2019MNRAS.484.5330J 2019MNRAS.484.5330J (SIMBAD/NED BibCode)
ADC_Keywords: Gravitational lensing; Photometry, ugriz; Redshifts
Keywords: gravitational lensing: strong; methods: statistical
Abstract:
We search Dark Energy Survey (DES) Year 3 imaging data for
galaxy-galaxy strong gravitational lenses using convolutional neural
networks. We generate 250000 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, rmag>19, g_mag>20, and imag>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.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table4.dat 62 84 New candidates from visual inspection of the
neural network-selected sources
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See also:
II/357 : The Dark Energy Survey (DES): Data Release 1 (Abbott+, 2018)
II/371 : The Dark Energy Survey (DES): Data Release 2 (Abott+, 2021)
J/ApJ/690/1236 : COSMOS photometric redshift catalog (Ilbert+, 2009)
J/MNRAS/413/813 : ATLAS3D project. I. (Cappellari+, 2011)
J/ApJ/749/38 : CFHTLS-SL2S-ARCS strong lens candidates (More+, 2012)
J/ApJ/785/144 : SL2S galaxy-scale sample of lens candidates (Gavazzi+, 2014)
J/MNRAS/465/4914 : R-band light curves of HE 0435-1223 (Bonvin+, 2017)
J/ApJS/232/15 : Candidate strong lens systems from DES obs. (Diehl+, 2017)
J/ApJS/243/17 : Strong DES lens cand. from neural networks (Jacobs+, 2019)
J/ApJS/259/27 : DES Bright Arcs Survey: strong lens syst. (O'Donnell+, 2022)
Byte-by-byte Description of file: table4.dat
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Bytes Format Units Label Explanations
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1- 3 A3 --- --- [DES]
4- 13 A10 --- DES System candidate designation (JHHMM+DDMM)
15- 23 I9 --- ObjID [66052645/507569548] Object identifier from DES
25- 32 F8.4 deg RAdeg Right ascension in decimal degrees (J2000)
34- 41 F8.4 deg DEdeg [-65.1/0.7] Declination in decimal degrees (J2000)
43- 46 F4.2 --- Grade [1/3] Grade (3=most certainly containing a
lens) (1)
48- 52 F5.2 mag imag [18.69/22.57] i-band magnitude
54- 57 F4.2 --- zphot [0.43/0.86] Photometric redshift
59- 62 F4.2 --- e_zphot [0.28/0.48] zphot uncertainty
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Note (1): We manually examine images with scores greater than a chosen
threshold and grade them 0-3, where 0=not a lens, 1=possibly a
lens, 2=probably a lens, and 3=definitely a lens. See Section 3.
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History:
From electronic version of the journal
(End) Emmanuelle Perret [CDS] 09-Jun-2022