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Advanced AI Discovers a Treasure Trove of Gravitational Lenses

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A selection of gravitational lenses identified by a machine-learning algorithm.

Credit: AGEL Survey

Australian researchers have identified potential gravitational lenses in images taken by the Dark Energy Camera on the Victor M. Blanco 4-m telescope at the Cerro Tololo Inter-American Observatory in Chile using a convolutional neural network. An algorithm developed by Colin Jacobs of the Swinburne University of Technology in Melbourne, Australia was used to identify a sample of 5,000 candidates of gravitational lenses (warps in space-time predicted by Albert Einstein) from tens of millions of galaxy images.

Researchers then studied 77 of the candidate lenses using the telescopes at the W.M. Keck Observatory in Hawaii and the Very Large Telescope in Chile, confirming 68 to be real. "With these lenses at different distances, we can look at different points in the cosmic timeline to track how things change over time, between the very first galaxies and now," said Kim-Vy Tran at ASTRO 3D and the University of New South Wales.

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