![]() ![]() Tran et al./The Astronomical Journal (2022). Each panel includes the confirmed distance to the foreground galaxy (z def) and distant background galaxy (z src). The pictures are centered on the foreground galaxy and include the object name. ![]() ![]() Pictures of gravitational lenses from the AGEL survey. The algorithm was developed by researcher Colin Jacobs at Swinburne University of Technology, who sifted through tens of millions of galaxy images to prune the sample down to 5000. “Our spectroscopy allowed us to map a 3D picture of the gravitational lenses to show they are genuine and not merely chance superposition,” professor Kim-Vy Tran said.Ī machine learning algorithm that searched for certain digital signatures made the work of Tran and the team possible. 11, 2022 - Researchers from the ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D) and the University of New South Wales (UNSW) Sydney spectroscopically confirmed a number of strong gravitational lenses that were initially identified using convolutional neural networks (CNNs). ![]()
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