A group of astronomers from the universities of Groningen, Naples and Bonn has developed a method that finds gravitational lenses in enormous piles of observations. The researchers published their method and 56 new gravitational lens candidates in the November issue of Monthly Notices of the Royal Astronomical Society. The astronomers trained the neural network using millions of homemade images of gravitational lenses. Initially, the neural network found 761 gravitational lens candidates. In the future, the researchers want to train their neural network even better so that it notices smaller lenses and rejects false ones. Explore further: Discovery of a rare quadruple gravitational lens candidate with Pan-STARRS. More information: C. E. Petrillo et al.
Finding strong gravitational lenses in the Kilo Degree Survey with Convolutional Neural Networks, Monthly Notices of the Royal Astronomical Society.