The first photo of a black hole looks like a ‘thin’ donut

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The first photo ever taken of a black hole looks a bit sharper now.

Originally released in 2019the unprecedented Historic image of the supermassive black hole at the center of the galaxy Messier 87 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 nicknamed the object the “fuzzy orange donut.”

Now, the scientists have used machine learning to give the image a cleaner update that looks more like a “thin” donut, 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 unseen heart of the massive galaxy Messier 87, or M87, near the Virgo cluster of galaxies, 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 worked on the project for more than a decade. The project got its name from the event horizon, the proposed boundary around a black hole that represents the point of no return where light or radiation cannot escape.

To capture an image of the black hole, scientists combined the power of seven radio telescopes from around the world using very long baseline interferometry, according to the European Southern Observatory, which is part of the EHT. this array it effectively created a virtual telescope 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, was released on thursday in The letters of the astrophysical journal.

“With our new machine learning technique, PRIMO, we were able to achieve the maximum resolution of the current array,” said study lead author Lia Medeiros, a postdoctoral fellow in astrophysics in the Faculty of Natural Sciences at the Institute for Advanced Study in Princeton, New Jersey, in a statement.

“Since we can’t study black holes up close, the detail in 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 a factor of two, which will be a powerful constraint for our theoretical models and gravity tests.”

Medeiros and other EHT members developed principal component interferometric modeling, or COUSIN. The algorithm is based on dictionary learning in which computers create rules based on large amounts of material. If a computer is given a series of images of different bananas, combined with some training, it could tell whether or not an unknown image contains a banana.

Computers using PRIMO analyzed more than 30,000 high-resolution simulated images of black holes to pick out common structural details. This allowed machine learning to essentially fill in the gaps in 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 and Infrared Astronomy Research Laboratory, or NOIR Lab. “It provides a way to compensate for missing information about the object being observed, which is required to generate the image that would have been seen using a single, gigantic, Earth-sized radio telescope.”

Black holes are made up of enormous amounts of matter packed into a small area, according to POT, creating a massive gravitational field that pulls in everything around it, including light. These powerful celestial phenomena also have a way of superheating the material around them and warping space-time.

Material accumulates around black holes, heating up to billions of degrees and reaching almost the speed of light. The light is bent around the black hole’s gravity, creating the ring of photons seen in the image. The shadow of the black hole is represented by the dark central region.

Visual confirmation of black holes also acts as confirmation of Albert Einstein’s theory of general relativity. In theory, Einstein predicted that dense, compact regions of space would have gravity so strong that nothing could escape them. But if hot plasma-like materials surround the black hole and emit light, the event horizon could be visible.

The new image may help scientists make more precise measurements of the black hole’s mass. Investigators can also apply PRIMO to other EHT observations, including those of the black hole in the center of our galaxy, the Milky Way.

“The 2019 image was just the beginning,” Medeiros said. “If a picture is worth a thousand words, the data underlying that picture has many more stories to tell. PRIMO will continue to be a fundamental tool for extracting such insights.”