Astronomers have used machine learning to sharpen the 2019 Event Horizon Telescope image of the black hole M87*, the first direct image of a black hole ever taken.
The first-ever photo of a supermassive black hole has gotten a"maximum resolution" makeover, thanks to artificial intelligence .
Now, a new effort has used machine learning to clean the image, sharpening it to achieve the fullest resolution possible and exposing a larger and darker central region surrounded by glowing gas that astronomers have described as a"skinny donut." The researchers published the updated image April 13 in The Astrophysical Journal Letters .
"With our new machine learning technique, PRIMO, we were able to achieve the maximum resolution of the current [telescope] array," lead author Lia Medeiros , an astronomer at the Institute for Advanced Study in Princeton, New Jersey, said in a statement."Since we cannot study black holes up-close, the detail of an image plays a critical role in our ability to understand its behavior.
To sharpen the picture, the researchers turned to a new AI technique called principal-component interferometric modeling , which analyzed more than 30,000 high-fidelity simulated images of black hole gas accretions to find common patterns. These patterns were then sorted by how commonly they occurred before being blended together and applied to the original image to produce a sharper estimate.
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