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  • Searching for strong lenses in Kilo Degree survey with Convolutional Neural Networks

    Title: Searching for strong lenses in Kilo Degree survey with Convolutional Neural Networks

    Speaker: LI Rui (SYSU) 

    Time: 14:00pm, Nov. 4 (Wednesday)

    Location: Room 516  No.5  building , Xianlin campus (PMO, CAS)

    Abstract: Strong lensing (SL) is the effect of the  deformation of light of background galaxies due to the gravitational potential  of intervening systems which act as lenses or “deflectors” (usually galaxies or  galaxy groups/clusters). This effect, predicted by general relativity, manifests  itself with the creation of spectacular arcs or multiple point images around the  deflectors. SLs can measure the mass of the deflectors with much high accuracy  than any of other methods, making it particularly suitable for studying a large number of astrophysical and cosmological open questions. However, at present,   the known and confirmed SLs are just a few hundreds, far from enough for probing  the scientific topics mentioned above with large statistical samples. Now, we have a great opportunity to enlarged the SL sample. The ongoing (e.g. Kilo Degree Survey, KiDS; Dark Energy survey, DES; Hyper Suprime-Cam, HSC;) and the next generation sky surveys (e.g., Large Synoptic Survey Telescope, LSST; Euclid; Chinese Space Station Telescope, CSST) provide us large database of galaxies (Millions to Billions) from which we expect to find a great number of SLs (~10^5). We are working on searching SLs in sky surveys with Machine Learnig. In this talk, I will introduce the new progress we have made in the lens searching work. I will also talk about two of our new findings: 1.first discovery of post-blue nugget galaxies through strong lensing. 2. Two strong lenses in one cluster. 


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