دورية أكاديمية
Identification of Galaxy–Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning
| العنوان: | Identification of Galaxy–Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning |
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| المؤلفون: | 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, E. J., 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, Dominique, 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., Carnero Rosell, A., Carrasco Kind, M., 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., Weaverdyck, N. |
| المصدر: | Astrophysical Journal, 954 (1), 68 (2023-08-23) |
| بيانات النشر: | American Astronomical Society, 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Space and Planetary Science, Astronomy and Astrophysics, Physical, chemical, mathematical & earth Sciences, Space science, astronomy & astrophysics, Physique, chimie, mathématiques & sciences de la terre, Aérospatiale, astronomie & astrophysique |
| الوصف: | 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, which contains ∼520 million astronomical sources covering ∼4000 deg2 of the southern sky to a 5σ 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 Dark Energy Camera data, we apply color and magnitude cuts to select a catalog of ∼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 (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 (decl. < 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 that 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. |
| نوع الوثيقة: | journal article http://purl.org/coar/resource_type/c_6501Test article peer reviewed |
| اللغة: | English |
| العلاقة: | info:eu-repo/grantAgreement/EC/H2020/787886; https://iopscience.iop.org/article/10.3847/1538-4357/ace4baTest; urn:issn:0004-637X; urn:issn:1538-4357 |
| DOI: | 10.3847/1538-4357/ace4ba |
| الوصول الحر: | https://orbi.uliege.be/handle/2268/306055Test |
| حقوق: | restricted access http://purl.org/coar/access_right/c_16ecTest info:eu-repo/semantics/restrictedAccess |
| رقم الانضمام: | edsorb.306055 |
| قاعدة البيانات: | ORBi |
| DOI: | 10.3847/1538-4357/ace4ba |
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