9/5/2023 0 Comments Blackhole pictures“Our thinking-and rightfully so-was that this is the very first time that anybody has seen a black hole, and we really wanted to not make any assumptions about that,” says Lia Medeiros, an astrophysicist at the Institute for Advanced Study in Princeton, N.J., and an author of the new research, who also helped create the 2019 image. But the ring’s blurriness made learning more about the black hole difficult. (Such a system, for instance, might decide that two neighboring pixels are more likely to be about the same brightness rather than vastly different.) When a distinctive ring-shaped image emerged from that process, that helped convince scientists that they were truly looking at a black hole. When scientists created the initial image, they relied on a generic machine-learning system to fill in the gaps. Behind both the 2019 original and today’s enhanced view of M87’s black hole are imaging techniques that use machine learning to act as a sort of “mathematical detective,” says Kazunori Akiyama, an astrophysicist at the Massachusetts Institute of Technology’s Haystack Observatory, who is a member of the Event Horizon Telescope Collaboration but did not take part in the new research. The 2019 image and its new companion were both based on data gathered from only a handful of locations on the planet, leaving big gaps in scientists’ view of the black hole. 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.īut the EHT has a fundamental problem: its data are spotty, like a scene observed through a dirty window where light streamed through only a few patches. That behemoth is one of two main targets of the Event Horizon Telescope (EHT), a coalition of radio observatories located around the globe. At its heart is a black hole that contains some 6.5 billion times the mass of our sun. The galaxy M87 is located some 54 million light-years away from Earth. “This is a beautiful example of how things can improve, how you can see further, how you can see sharper, literally,” she says. “I think they really are in this nice niche where you develop a specific algorithm for a specific problem and put in physical knowledge and make significant progress,” says Tiziana Di Matteo, an astrophysicist at Carnegie Mellon University, who uses machine learning in her own work and wasn’t involved in the new research. The new image lays the groundwork for future advances in our understanding of black holes, scientists say. But research published in the Astrophysical Journal Letters on April 13 sharpens that view into a narrow ring against a stark, black background. The picture that captivated the world in 2019 showed a bright, blurry doughnut of light. ![]() ![]() ![]() The iconic first-ever view of a supermassive black hole sports a dramatic new look, thanks to machine learning.
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