The AGEL Survey: Spectroscopic Confirmation of Strong Gravitational Lenses in the DES and DECaLS Fields Selected Using Convolutional Neural Networks
Kim-Vy H. Tran, Anishya Harshan, Karl Glazebrook, G.C. Keerthi Vasan,, Tucker Jones, Colin Jacobs, Glenn G. Kacprzak, Tania M. Barone, Thomas E., Collett, Anshu Gupta, Astrid Henderson, Lisa J. Kewley, Sebastian Lopez,, Themiya Nanayakkara, Ryan L. Sanders, Sarah M. Sweet

TL;DR
The AGEL survey confirms that CNN-based methods effectively identify strong gravitational lenses at higher redshifts using deep imaging and spectroscopy, providing a valuable resource for future astrophysical and cosmological studies.
Contribution
This study demonstrates the high success rate of CNN-based searches in identifying strong gravitational lenses and provides spectroscopic redshifts for a significant sample, expanding the known lens population.
Findings
CNN search methods are 88% successful in identifying lenses.
Spectroscopic redshifts measured for 68 lenses, with sources at z>1.34.
The survey includes 41 deflectors at z>0.5 suitable for follow-up studies.
Abstract
We present spectroscopic confirmation of candidate strong gravitational lenses using the Keck Observatory and Very Large Telescope as part of our ASTRO 3D Galaxy Evolution with Lenses (AGEL) survey. We confirm that 1) search methods using Convolutional Neural Networks (CNN) with visual inspection successfully identify strong gravitational lenses and 2) the lenses are at higher redshifts relative to existing surveys due to the combination of deeper and higher resolution imaging from DECam and spectroscopy spanning optical to near-infrared wavelengths. We measure 104 redshifts in 77 systems selected from a catalog in the DES and DECaLS imaging fields (r<22 mag). Combining our results with published redshifts, we present redshifts for 68 lenses and establish that CNN-based searches are highly effective for use in future imaging surveys with a success rate of 88% (defined as 68/77). We…
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