Using Machine Learning to Find Gravitationally-Lensed Quasars and Supernovae

大型综合巡天望远镜（LSST）将在本世纪20年代的强引力透镜革命中发挥主要作用。LSST将能够探测到数以万计的新的强引力透镜事件（例如Collett 2015），这要归功于它预期的图像质量（0.6英寸FWHM，包括望远镜、大气和风）。这些透镜将是欧几里得和其他巡天探测到的透镜的补充，LSST探测的是一个更微弱的源群，受益于多色数据和非常适合透镜类星体和SNe发现的节奏。

The Large Synoptic Survey Telescope (LSST) will play a main role in revolutionising strong gravitational lensing in the 2020s. LSST will be able to detect many tens of thousands of new strong gravitational lens events (e.g. Collett 2015), thanks to its expected image quality (0.6'' FWHM including telescope, atmosphere and wind). These lenses will be complementary to those detected by Euclid and other surveys, with LSST probing a much fainter source population and benefitting both from multicolour data and a cadence well-suited to lensed quasar and SNe discovery.