http://arxiv.org/abs/1807.02845
Context: Strong gravitational lensing represents an invaluable tool for answering some of the most important questions from cosmology. It however strongly depends on the availability of a statistically significant number of lenses, coming along with sufficient constraints to model each system in a realistic way. Still, the number of currently known quadruply-imaged systems remains very limited, mostly because of their scarcity and to inherent difficulties in identifying them amongst extremely large catalogues along with a sufficiently low misclassification rate.
Aims: In this work, we aim to provide a reliable list of gravitational lens candidates coming from a blind search analysis performed over the entire Gaia Data Release 2 (Gaia DR2). We also aim to show that the sole astrometric and photometric informations coming from the Gaia satellite yield sufficient insights for supervised learning methods to automatically identify strong gravitational lens candidates with an efficiency that is comparable to methods based on image processing.
Results: We report the discovery of 15 new quadruply-imaged lens candidates with angular separations less than 6″ and assess the performances of our approach by recovering 11 out of the 12 known quadruply-imaged systems having all their components detected in Gaia DR2 with a misclassification rate of fortuitous clusters of stars as lens systems that is below one percent. Similarly, the identification capability of our method regarding quadruply-imaged systems where three images are detected in Gaia DR2 is assessed by recovering 9 out of the 12 known quadruply-imaged systems having one of their constituting images being discarded. The associated misclassification rate varying then between 5.83% and 20%, depending on the image we decided to remove.
L. Delchambre, A. Krone-Martins, O. Wertz, et. al.
Tue, 10 Jul 18
13/79
Comments: 11 pages, 4 figures, 4 tables
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