Researchers used machine learning to improve the first photo of a black hole

Researchers have used machine learning to tighten up a previously released image of a black hole. As a result, the portrait of the black hole at the center of the galaxy Messier 87, over 53 million light years away from Earth, shows a thinner ring of light and matter surrounding its center in a report published today in The Astrophysical Journal Letters. The original images were captured in 2017 by the Event Horizon Telescope (EHT), a network of radio telescopes around Earth that combine to act as a planet-sized super-imaging tool. The initial picture looked like a "fuzzy donut," as described by NPR, but researchers used a new method called PRIMO to reconstruct a more accurate image. PRIMO is "a novel dictionary-learning-based algorithm" that learns to "recover high-fidelity images even in the presence of sparse coverage" by training on generated simulations of over 30,000 black holes.