LinKS: discovering galaxy-scale strong lenses in the Kilo-Degree Survey using convolutional neural networks
文献类型：期刊论文
| 作者 | Petrillo, C. E.2; Tortora, C.2,3; Vernardos, G.2; Koopmans, L. V. E.2; Kleijn, G. Verdoes2; Bilicki, M.4,5; Napolitano, N. R.6; Chatterjee, S.2; Covone, G.1; Dvornik, A.4 |
| 刊名 | MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
 |
| 出版日期 | 2019-04-01 |
| 卷号 | 484期号:3页码:3879-3896 |
| ISSN号 | 0035-8711 |
| 关键词 | gravitational lensing: strong galaxies: elliptical and lenticular,CD |
| DOI | 10.1093/mnras/stz189 |
| 英文摘要 | We present a new sample of galaxy-scale strong gravitational lens candidates, selected from 904 deg(2) of Data Release 4 of the Kilo-Degree Survey, i.e. the 'Lenses in the KiloDegree Survey' (LinKS) sample. We apply two convolutional neural networks (ConvNets) to similar to 88000 colour-magnitude-selected luminous red galaxies yielding a list of 3500 strong lens candidates. This list is further downselected via human inspection. The resulting LinKS sample is composed of 1983 rank-ordered targets classified as 'potential lens candidates' by at least one inspector. Of these, a high-grade subsample of 89 targets is identified with potential strong lenses by all inspectors. Additionally, we present a collection of another 200 strong lens candidates discovered serendipitously from various previous ConvNet runs. A straightforward application of our procedure to future Euclid or Large Synoptic Survey Telescope data can select a sample of similar to 3000 lens candidates with less than 10 per cent expected false positives and requiring minimal human intervention. |
| 资助项目 | NWO-VICI grant[639.043.308] ; INAF PRIN-SKA 2017 program[1.05.01.88.04] ; Netherlands Organization for Scientific Research (NWO)[614.001.206] ; Netherlands Organization for Scientific Research (NWO)[621.016.402] ; Netherlands Research School for Astronomy (NOVA) ; Target ; Samenwerkingsverband Noord Nederland ; European fund for regional development ; Dutch Ministry of economic affairs ; Pieken in de Delta ; Province of Groningen ; Province of Drenthe ; European Union Horizon 2020 research and innovation programme under the Marie SklodowskaCurie grant[721463] ; Deutsche Forschungsgemeinschaft ; Polish Ministry of Science and Higher Education[DIR/WK/2018/12] ; European Research Council[647112] ; Alexander von Humboldt Foundation ; European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie actions grant[664931] ; La Silla Paranal Observatory[177.A-3016] ; La Silla Paranal Observatory[177.A-3017] ; La Silla Paranal Observatory[177.A-3018] ; NOVA grant ; NWO-M grant ; Department of Physics and Astronomy of the University of Padova ; STFC (UK) ; ARC (Australia) ; AAO ; Alfred P. Sloan Foundation ; US Department of Energy Office of Science ; Center for High-Performance Computing at the University of Utah ; Brazilian Participation Group ; Carnegie Institution for Science ; Carnegie Mellon University ; Chilean Participation Group ; French ParticipationGroup ; Harvard-Smithsonian Center forAstrophysics ; Instituto de Astrofisica de Canarias ; Johns Hopkins University ; Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo ; Korean Participation Group ; Lawrence Berkeley National Laboratory ; Leibniz Institut fur Astrophysik Potsdam (AIP) ; Max-Planck-Institut fur Astronomie (MPIA Heidelberg) ; Max-Planck-Institut fur Astrophysik (MPAGarching) ; Max-Planck-Institut fur Extraterrestrische Physik (MPE) ; National Astronomical Observatories of China ; New Mexico State University ; New York University ; University of Notre Dame ; Observatorio Nacional/MCTI ; Ohio State University ; Pennsylvania State University ; Shanghai Astronomical Observatory ; United Kingdom Participation Group ; Universidad Nacional Autonoma de Mexico ; University of Arizona ; University of Colorado Boulder ; University of Oxford ; University of Portsmouth ; University of Utah ; University of Virginia ; University of Washington ; University of Wisconsin ; Vanderbilt University ; Yale University ; Netherlands Organization for Scientific Research, NWO[614.001.451] |
| WOS研究方向 | Astronomy & Astrophysics |
| 语种 | 英语 |
| 出版者 | OXFORD UNIV PRESS |
| WOS记录号 | WOS:000462410300076 |
| 源URL | [http://119.78.226.72/handle/331011/31851]  |
| 专题 | 中国科学院上海天文台 |
| 通讯作者 | Petrillo, C. E. |
| 作者单位 | 1.Univ Napoli Federico II, Dipartimento Sci Fis, Compl Univ Monte S Angelo, I-80126 Naples, Italy 2.Univ Groningen, Kapteyn Astron Inst, Postbus 800, NL-9700 AV Groningen, Netherlands 3.INAF, Osservatorio Astrofis Arcetri, Largo Enrico Fermi 5, I-50125 Florence, Italy 4.Leiden Univ, Leiden Observ, POB 9513, NL-2300 RA Leiden, Netherlands 5.Polish Acad Sci, Ctr Theoret Phys, Al Lotnikow 32-46, PL-02668 Warsaw, Poland 6.INAF, Osservatorio Astron Capodimonte, Salita Moiariello 16, I-80131 Naples, Italy 7.Argelander Inst Astron, Hugel 71, D-53121 Bonn, Germany 8.Univ Edinburgh, Inst Astron, Royal Observ, Blackford Hill, Edinburgh EH9 3HJ, Midlothian, Scotland 9.Shanghai Astron Observ SHAO, Nandan Rd 80, Shanghai 200030, Peoples R China |
| 推荐引用方式 GB/T 7714 | Petrillo, C. E.,Tortora, C.,Vernardos, G.,et al. LinKS: discovering galaxy-scale strong lenses in the Kilo-Degree Survey using convolutional neural networks[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2019,484(3):3879-3896. |
| APA | Petrillo, C. E..,Tortora, C..,Vernardos, G..,Koopmans, L. V. E..,Kleijn, G. Verdoes.,...&Wright, A. H..(2019).LinKS: discovering galaxy-scale strong lenses in the Kilo-Degree Survey using convolutional neural networks.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,484(3),3879-3896. |
| MLA | Petrillo, C. E.,et al."LinKS: discovering galaxy-scale strong lenses in the Kilo-Degree Survey using convolutional neural networks".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 484.3(2019):3879-3896. |
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来源：上海天文台
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