| Using Convolutional Neural Networks to Search for Strongly Lensed Quasars in KiDS DR5 | |
He, Zizhao1; Li, Rui2; Shu, Yiping1; Tortora, Crescenzo3; Er, Xinzhong4; Cañameras, Raoul5,6,7; Schuldt, Stefan8,9; Napolitano, Nicola R.10,11,12; N, Bharath Chowdhary13; Chen, Qihang14,15; Li, Nan9,16; Feng HC(封海成)17 ; Deng, Limeng1,18; Li, Guoliang1; Koopmans, L. V. E.13; Dvornik, Andrej19
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| 发表期刊 | ASTROPHYSICAL JOURNAL
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| 2025-03-10 | |
| 卷号 | 981期号:2 |
| DOI | 10.3847/1538-4357/adaf28 |
| 产权排序 | 第17完成单位 |
| 收录类别 | SCI |
| 摘要 | Gravitationally strongly lensed quasars (SL-QSO) offer invaluable insights into cosmological and astrophysical phenomena. With the data from ongoing and next-generation surveys, thousands of SL-QSO systems can be discovered expectedly, leading to unprecedented opportunities. However, the challenge lies in identifying SL-QSO from enormous data sets with high recall and purity in an automated and efficient manner. Hence, we developed a program based on a convolutional neural network (CNN) for finding SL-QSO from large-scale surveys and applied it to the Kilo-degree Survey Data Release 5. Our approach involves three key stages: first, we preselected 10 million bright objects (with r-band MAG_AUTO < 22), excluding stars from the data set; second, we established realistic training and test sets to train and fine-tune the CNN, resulting in the identification of 4195 machine candidates, and the false-positive rate of similar to 1/2000 and recall of 0.8125 evaluated by using the real test set containing 16 confirmed lensed quasars; third, human inspections were performed for further selections, and then, 272 SL-QSO candidates were eventually found in total, including 16 high-score, 118 median-score, and 138 lower-score candidates, separately. Removing the systems already confirmed or identified in other papers, we end up with 229 SL-QSO candidates, including 7 high-score, 95 median-score, and 127 lower-score candidates, and the corresponding catalog is publicly available online (https://github.com/EigenHermit/H24). We have also included an excellent quad candidate in the Appendix, discovered serendipitously during the fine-tuning process of the CNN. |
| 资助项目 | China Postdoctoral Foundation Project divided by National Postdoctoral Program for Innovative Talents (Postdoctoral Innovation Talent Support Program of China)https://doi.org/10.13039/501100012152 |
| 项目资助者 | China Postdoctoral Foundation Project divided by National Postdoctoral Program for Innovative Talents (Postdoctoral Innovation Talent Support Program of China)https://doi.org/10.13039/501100012152 |
| 语种 | 英语 |
| 学科领域 | 天文学 ; 星系与宇宙学 |
| 文章类型 | Article |
| 出版者 | IOP Publishing Ltd |
| 出版地 | TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND |
| ISSN | 0004-637X |
| URL | 查看原文 |
| WOS记录号 | WOS:001439096100001 |
| WOS研究方向 | Astronomy & Astrophysics |
| WOS类目 | Astronomy & Astrophysics |
| 关键词[WOS] | KILO-DEGREE SURVEY ; STRONG GRAVITATIONAL LENSES ; HSC IMAGING SUGOHI ; DIGITAL SKY SURVEY ; BROAD-LINE REGION ; SPACE-TELESCOPE ; HUBBLE CONSTANT ; INDEPENDENT DETERMINATION ; CIRCUMGALACTIC MEDIUM ; SPECTROSCOPY SURVEY |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 版本 | 出版稿 |
| 条目标识符 | http://ir.ynao.ac.cn/handle/114a53/28193 |
| 专题 | 南方基地 |
| 作者单位 | 1.Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing, Jiangsu, 210023, People's Republic of China; [email protected]; 2.Institute for Astrophysics, School of Physics, Zhengzhou University, Zhengzhou, 450001, People's Republic of China; [email protected]; 3.INAF – Osservatorio Astronomico di Capodimonte, Salita Moiariello 16, I-80131, Napoli, Italy; 4.Tianjin Astrophysics Center, Tianjin Normal University, Tianjin 300387, People's Republic of China; 5.Max-Planck-Institut für Astrophysik, Karl-Schwarzschild Straße 1, 85748 Garching, Germany; 6.Technical University of Munich, TUM School of Natural Sciences, Department of Physics, James-Franck-Straße 1, 85748 Garching, Germany; 7.Aix Marseille University, CNRS, CNES, LAM, Marseille, France; 8.Dipartimento di Fisica, Università degli Studi di Milano, via Celoria 16, I-20133 Milano, Italy; 9.INAF - IASF Milano, via A. Corti 12, I-20133 Milano, Italy; 10.School of Physics and Astronomy, Sun Yat-sen University, Zhuhai Campus, 2 Daxue Road, Xiangzhou District, Zhuhai, People's Republic of China; 11.CSST Science Center for Guangdong-Hong Kong-Macau Great Bay Area, Zhuhai, 519082, People's Republic of China; 12.INAF – Osservatorio Astronomico di Capodimonte, Salita Moiariello 16, 80131 - Napoli, Italy; 13.Kapteyn Astronomical Institute, University of Groningen, PO Box 800, NL-9700 AV Groningen, The Netherlands; 14.Department of Astronomy, Beijing Normal University, Beijing 100875, People's Republic of China; 15.Institute for Frontier in Astronomy and Astrophysics, Beijing Normal University, Beijing, 102206, People's Republic of China; 16.Key Laboratory of Space Astronomy and Technology, National Astronomical Observatories, CAS, Beijing 100101, People's Republic of China; 17.Yunnan Observatories, Chinese Academy of Sciences, Kunming 650216, Yunnan, People's Republic of China; 18.School of Astronomy and Space Sciences, University of Science and Technology of China, Hefei 230026, People's Republic of China; 19.Ruhr University Bochum, Faculty of Physics and Astronomy, Astronomical Institute (AIRUB), German Centre for Cosmological Lensing, 44780 Bochum, Germany |
| 推荐引用方式 GB/T 7714 | He, Zizhao,Li, Rui,Shu, Yiping,et al. Using Convolutional Neural Networks to Search for Strongly Lensed Quasars in KiDS DR5[J]. ASTROPHYSICAL JOURNAL,2025,981(2). |
| APA | He, Zizhao.,Li, Rui.,Shu, Yiping.,Tortora, Crescenzo.,Er, Xinzhong.,...&Dvornik, Andrej.(2025).Using Convolutional Neural Networks to Search for Strongly Lensed Quasars in KiDS DR5.ASTROPHYSICAL JOURNAL,981(2). |
| MLA | He, Zizhao,et al."Using Convolutional Neural Networks to Search for Strongly Lensed Quasars in KiDS DR5".ASTROPHYSICAL JOURNAL 981.2(2025). |
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| Using Convolutional （14537KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 请求全文 | |
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