First image of a black hole reworked with artificial intelligence
Eden Villalovas
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The supermassive black hole at the center of galaxy Messier 87 was revamped for the first time by a new machine-learning technique called PRIMO, or principal-component interferometric modeling. The redone image keeps the original shape of the black hole but increases the resolution, displaying a fuller center and narrower outer ring.
The image, published Thursday morning in the Astrophysical Journal Letters, will allow scientists to gain a better understanding of its characteristics and increase further research in additional galaxies, including the black hole at the heart of our Milky Way.
FIRST IMAGE OF A BLACK HOLE RELEASED
Creators of PRIMO, a team of researchers along with an astronomer with NSF’s NOIRLab, used data received from the Event Horizon Telescope, which created the original image in 2019, to create a high-quality resolution.
“With our new machine learning technique, PRIMO, we were able to achieve the maximum resolution of the current array,” Lia Medeiros said, lead author of the Institute for Advanced Study. “Since we cannot study black holes up-close, the detail of an image plays a critical role in our ability to understand its behavior. The width of the ring in the image is now smaller by about a factor of two, which will be a powerful constraint for our theoretical models and tests of gravity.”
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To rework the image, computers analyzed more than 30,000 simulated images of black holes accreting gas, searching for common patterns in the structure of the image, and blended them to create a model. The full algorithm explanation for PRIMO can be found in The Astrophysical Journal, published on Feb. 3.
“The 2019 image was just the beginning,” said Medeiros in the photo release. “If a picture is worth a thousand words, the data underlying that image have many more stories to tell. PRIMO will continue to be a critical tool in extracting such insights.”