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The first photo ever taken of a black hole now looks a little sharper.
Originally released in 2019, the unprecedented The historic image of the supermassive black hole at the center of the Messier 87 galaxy has captured an essentially invisible celestial object. using direct images.
The image presented the first direct visual evidence that black holes exist, showing a dark central region encapsulated by a ring of light that appears brighter on one side. Astronomers have dubbed the object the “fuzzy, orange donut.”
Now, scientists have used machine learning to give the image a cleaner update that looks more like a “skinny” doughnut, the researchers said. The central region is darker and larger, surrounded by a bright ring as hot gas falls into the black hole in the new image.
In 2017, astronomers set out to observe the invisible core of the massive galaxy Messier 87, or M87, near the Virgo galaxy cluster 55 million light years from Earth.
The Event Horizon Telescope Collaboration, called EHT, is a global network of telescopes that captured the first photograph of a black hole. More than 200 researchers have worked on the project for more than a decade. The project was named for the event horizon, the proposed boundary around a black hole that represents the point of no return where no light or radiation can escape.
To capture an image of the black hole, scientists combined the power of seven radio telescopes around the world with very long baseline interferometry, according to the European Southern Observatory, which is part of the EHT. This array effectively created a virtual telescope around the same size as Earth.
Data from the original 2017 observation was combined with a machine learning technique to capture the full resolution of what the telescopes saw for the first time. The new, more detailed image, along with a study, has been released Thursday in The Astrophysical Journal Letters.
“With our new machine learning technique, PRIMO, we were able to achieve the maximum resolution of the current array,” said the study’s lead author Lia Medeiros, a postdoctoral astrophysicist at the School of Natural Sciences in l ‘Institute of Advanced Studies in Princeton, New Jersey, 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 their behavior. The width of the ring in the image is now smaller by about a factor of two, which will be a powerful force for our theoretical models and tests of gravity.”
Medeiros and other members of the EHT developed Interferometric Modeling of Principal Components, or FIRST. The algorithm is based on dictionary learning in which computers create rules based on a large amount of material. If a computer is given a series of images of different bananas, combined with some training, it might be able to tell whether an unknown image does or does not contain a banana.
Computers using PRIMO analyzed more than 30,000 simulated high-resolution images of black holes to pick out common structural details. This allowed machine learning to essentially fill in the gaps of the original image.
“PRIMO is a new approach to the difficult task of building images from EHT observations,” said Tod Lauer, an astronomer at the National Science Foundation’s National Optical-Infrared Astronomy Research Laboratory, or NOIRLab. “It provides a way to compensate for the missing information about the observed object, which is necessary to generate images that would have been seen with a single giant radio telescope the size of the Earth.”
Black holes consist of huge amounts of matter squeezed into a small area, according to him NASA, creating a massive gravitational field that pulls in everything around, including light. These powerful celestial phenomena also have a way of overheating the material around them and warping space-time.
Material accumulates around black holes, is heated to billions of degrees and reaches almost the speed of light. The light bends around the black hole’s gravity, which creates the ring of photons seen in the image. The shadow of the black hole is represented by the dark central region.
The visual confirmation of black holes also acts as a confirmation of Albert Einstein’s theory of general relativity. In theory, Einstein predicted that dense, compact regions of space would have such intense gravity that nothing could escape. But if heated materials in the form of plasma surround the black hole and emit light, the event horizon could be visible.
The new image may help scientists make more accurate measurements of the black hole’s mass. Researchers can also apply PRIMO to other EHT observations, including those of the black hole at the center of our Milky Way galaxy.
“Imagine 2019 was just the beginning,” said Medeiros. “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.”
