(CNN) The first image ever taken of a black hole is now looking much clearer.
Originally released in 2019like never before Historic image of the supermassive black hole at the center of the galaxy Messier 87 captured essentially invisible celestial bodies using direct imaging.
The image provided the first direct visual evidence of the existence of black holes, showing a central dark region enveloped in a ring of light that appears brighter on one side. Astronomers dubbed the object the “fuzzy orange donut.”
Scientists have now used machine learning to give the image a cleaner upgrade that looks more like a “skinny” donut, the researchers said. The central region is darker and larger, surrounded by a bright ring where hot gas falls into the black hole in the new image.
Machine learning technology was used to improve the Event Horizon Telescope Collaboration’s image (left) of the supermassive black hole at the center of Messier 87, producing a sharper image.
In 2017, astronomers set out to observe the invisible 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 the EHT, is a global network of telescopes that took the first image of a black hole. More than 200 researchers have worked on the project for more than a decade. The project is named after the event horizon, the proposed boundary around a black hole that marks the point of no return where no light or radiation can escape.
To capture a picture of the black hole, scientists combined the power of seven radio telescopes around the world using very long interferometry, according to the European Southern Observatory, which is part of the EHT. this group He created a virtual telescope roughly the same size as the Earth.
Maximum Accuracy Achieved
Data from the original 2017 observation was combined with machine learning technology to capture the full resolution of what the telescopes saw for the first time. The new, more detailed image has been released with a study On Thursday in Astrophysical Journal Letters.
said lead study author Lia Medeiros, a postdoctoral fellow in astrophysics in the School of Natural Sciences at the Institute for Advanced Study at Princeton, New Jersey, in a statement.
“Because we cannot study black holes up close, the details of the image play an important role in our ability to understand their behavior. The width of the ring in the image is now about two times smaller, which will be a strong limitation for our theoretical models and gravity tests.”
Medeiros and other members of the EHT developed principal component interference modeling, or PRIMO. The algorithm is based on dictionary learning where computers create rules based on large amounts of material. If a computer is given a series of different banana pictures, plus some training, it might be able to tell whether or not the unknown picture 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 basically allowed the machine learning to fill in the gaps of the original image.
“PRIMO is a new approach to the challenging task of building images from EHT observations,” said Todd Lauer, an astronomer at the National Science Foundation’s Optical and Infrared Astronomy Research Laboratory. NOIRLab. “It provides a way to compensate for missing information about the object being monitored, which is required to generate the image that would have been seen with a single giant Earth-sized radio telescope.”
Developing black hole research
Black holes are made of huge amounts of matter crammed into a small region, according to him NASA, which creates a massive gravitational field that attracts everything around it, including light. These powerful celestial phenomena also have a way of heating up the matter around them and warping space-time.
Material accumulates around black holes, heated to billions of degrees and reaches almost the speed of light. The light is bent around the black hole’s gravity, resulting in the photon ring seen in the image. The black hole’s shadow is represented by the dark central region.
Optical confirmation of black holes also serves as confirmation of Albert Einstein’s general theory of relativity. In theory, Einstein predicted that dense and compact regions of space would have gravity so intense that nothing could escape from it. But if hot material in the form of plasma surrounds the black hole and emits light, the event horizon may be visible.
The new image could 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.
“Photo 2019 was just the beginning,” Medeiros said. “If a picture is worth a thousand words, the data behind that image has many more stories to tell. PRIMO will continue to be a critical tool in extracting such insights.”