The research is published in The Astrophysical Journal Letters. PRIMO will continue to be a critical tool in extracting such insights.” “If a picture is worth a thousand words, the data underlying that image have many more stories to tell. “The 2019 image was just the beginning,” said Medeiros. In 2022, the EHT collaboration followed up its image of the black hole in M87 with a stunning image of the black hole at the heart of the Milky Way, so that image could be the next target for sharpening using this technique. “It provides a way to compensate for the missing information about the object being observed, which is required to generate the image that would have been seen using a single gigantic radio telescope the size of the Earth.” “PRIMO is a new approach to the difficult task of constructing images from EHT observations,” said another of the researchers, Tod Lauer of NSF’s NOIRLab. The plan is that the same technique can be used for future observations from the EHT collaboration as well. By analyzing the pictures that resulted from these simulations for patterns, PRIMO was able to refine the data for the EHT image. This Is the First Picture of a Black Hole And Thats a Big, Even Supermassive, Deal. PRIMO was trained using tens of thousands of example images which were created from simulations of gas accreting onto a black hole. This black hole, with a mass 6.5 billion times that of our sun, was the subject of the first image of such an object ever obtained, released in 2019, with another black hole pictured last year. 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.” “Since we cannot study black holes up close, the detail in an image plays a critical role in our ability to understand its behavior. “With our new machine-learning technique, PRIMO, we were able to achieve the maximum resolution of the current array,” said lead author of the research, Lia Medeiros of the Institute for Advanced Study, in a statement. Medeiros (Institute for Advanced Study), D. The image of the M87 supermassive black hole originally published by the Event Horizon Telescope collaboration in 2019 (left) and a new image generated by the PRIMO algorithm using the same data set (right). The new machine learning approach has been used to fill in those gaps, which allows for a more sharp and more precise final image. While that approach was amazingly effective at seeing such a distant object located 55 million light-years away, it did mean that there were some gaps in the original data. That image combined data from seven radio telescopes around the globe which worked together to form a virtual Earth-sized array. The approach, called PRIMO or principal-component interferometric modeling, was developed by some of the same researchers that worked on the original Event Horizon Telescope project that took the photo of the black hole. Now, that image has been refined and sharpened using machine learning techniques. The world watched in delight when scientists revealed the first-ever image of a black hole in 2019, showing the huge black hole at the center of galaxy Messier 87.
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