1. Identification of Galaxy-Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning
- Author
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Zaborowski, E. A., Drlica-Wagner, A., Ashmead, F., Wu, J. F., Morgan, R., Bom, C. R., Shajib, A. J., Birrer, S., Cerny, W., Buckley-Geer, L., Mutlu-Pakdil, B., Ferguson, P. S., Glazebrook, K., Lozano, S. J. Gonzalez, Gordon, Y., Martinez, M., Manwadkar, V., O'Donnell, J., Poh, J., Riley, A., Sakowska, J. D., Santana-Silva, L., Santiago, B. X., Sluse, D., Tan, C. Y., Tollerud, E. J., Verma, A., Carballo-Bello, J. A., Choi, Y., James, D. J., Kuropatkin, N., Martínez-Vázquez, C. E., Nidever, D. L., Castellon, J. L. Nilo, Noël, N. E. D., Olsen, K. A. G., Pace, A. B., Mau, S., Yanny, B., Zenteno, A., Abbott, T. M. C., Aguena, M., Alves, O., Andrade-Oliveira, F., Bocquet, S., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Conselice, C. J., Costanzi, M., Pereira, M. E. S., De Vicente, J., Desai, S., Dietrich, J. P., Doel, P., Everett, S., Ferrero, I., Flaugher, B., Friedel, D., Frieman, J., García-Bellido, J., Gruen, D., Gruendl, R. A., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Kuehn, K., Lin, H., Marshall, J. L., Melchior, P., Mena-Fernández, J., Menanteau, F., Miquel, R., Palmese, A., Paz-Chinchón, F., Pieres, A., Malagón, A. A. Plazas, Prat, J., Rodriguez-Monroy, M., Romer, A. K., Sanchez, E., Scarpine, V., Sevilla-Noarbe, I., Smith, M., Suchyta, E., To, C., and Weaverdyck, N.
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Astrophysics - Astrophysics of Galaxies - Abstract
We perform a search for galaxy-galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey (DELVE), which contains $\sim 520$ million astronomical sources covering $\sim 4,000$ $\mathrm{deg}^2$ of the southern sky to a $5\sigma$ point-source depth of $g=24.3$, $r=23.9$, $i=23.3$, and $z=22.8$ mag. Following the methodology of similar searches using DECam data, we apply color and magnitude cuts to select a catalog of $\sim 11$ million extended astronomical sources. After scoring with our CNN, the highest scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (definitely not a lens) to 3 (very probable lens). We present a list of 581 strong lens candidates, 562 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 55 Grade A candidates, 149 Grade B candidates, and 377 Grade C candidates. We additionally highlight eight potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap ($b > 10$ deg) and southern celestial hemisphere (${\rm Dec.}<0$ deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprint does overlap with other searches, we find a significant number of high-quality candidates which were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation., Comment: 24 pages; published version (ApJ)
- Published
- 2022
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