Using machine learning, researchers have now created a much sharper portrait of the supermassive black hole at the center of the galaxy M87
The iconic first-ever view of a supermassive black hole sports a dramatic new look, thanks to machine learning.
The galaxy M87 is located some 54 million light-years away from Earth. At its heart is a black hole that contains some 6.5 billion times the mass of our sun. That behemoth is one of two main targets of the Event Horizon Telescope , a coalition of radio observatories located around the globe. By combining data from these sources, scientists essentially constructed a telescope the size of Earth—powerful enough to capture details of bright matter swirling around the black hole.
When scientists created the initial image, they relied on a generic machine-learning system to fill in the gaps. When a distinctive ring-shaped image emerged from that process, that helped convince scientists that they were truly looking at a black hole. But the ring’s blurriness made learning more about the black hole difficult.
PRIMO runs on rules derived from what scientists expect black holes to look like, which the algorithm gleaned from training on a host of simulated black holes with varying characteristics—different masses, different spins, and so on. The result is a much more specialized algorithm.
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