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You are at:Home»Health»The first photo of a black hole is similar to the ‘thin’ donut
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The first photo of a black hole is similar to the ‘thin’ donut

Nana MediaBy Nana MediaMay 10, 20253 Mins Read
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The first photo of a black hole is similar to the ‘thin’ donut
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Introduction to Black Holes

The first photo of a black hole, which was initially published in 2019, has been upgraded with the help of machine learning, making it look sharper and more detailed. This historical picture of the supermassive black hole was captured using direct imaging and provided the first direct visual evidence of the existence of black holes.

The Initial Discovery

The picture, which was taken by the Event Horizon Telescope (EHT), a global network of telescopes, shows a central dark region surrounded by a light ring that is brighter on one side. Astronomers referred to the object as a "fuzzy, orange donut." The EHT is a project that involves more than 200 researchers who have worked together for over a decade to capture the first image of a black hole.

The Upgrade

Now, scientists have used machine learning to give the picture a cleaner upgrade, making it look more like a "thin" donut. The central region is darker and larger, surrounded by a light ring, as hot gas falls into the black hole. This new image provides a more detailed look at the black hole and its surroundings, allowing scientists to study it more effectively.

The Technology Behind the Image

The EHT is a global network of telescopes that work together to form a virtual telescope the size of the Earth. This array is capable of capturing high-resolution images of black holes, which are incredibly far away from us. The data from the original observation in 2017 was combined with a machine learning technique to achieve the full resolution of what the telescope saw for the first time.

Machine Learning Technique

The machine learning technique used to upgrade the image is called Primo, which is based on dictionary learning. This algorithm allows computers to create rules based on large amounts of material, making it possible to fill in the gaps in the original image. Computers with Primo analyzed over 30,000 high-resolution simulated pictures of black holes to select common structural details, making it possible for machine learning to essentially fill in the gaps in the original image.

Understanding Black Holes

Black holes are regions of space where the gravitational pull is so strong that nothing, including light, can escape. They are formed when a massive star collapses in on itself, creating a massive amount of matter in a small area. The material surrounding black holes is heated to billions of degrees and almost reaches the speed of light, creating a photon ring that can be seen in the picture. The shadow of the black hole is shown by the dark central region.

Confirmation of Einstein’s Theory

The visual confirmation of black holes also acts as a confirmation of Albert Einstein’s theory of general relativity. According to Einstein’s theory, density, compact regions of space would have such intensive gravity that nothing could escape them. The new picture can help scientists make more precise measurements of the mass of the black hole and apply Primo to other observations, including that of the black hole in the center of our Milky Way.

Future Research

The new picture is just the beginning, and the data on which this image is based has many more stories to tell. Primo is a critical tool to extract such findings, and scientists can apply it to other observations to gain a deeper understanding of black holes and the universe. With this new technology, scientists can continue to study black holes and make new discoveries that can help us better understand the universe.

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