Scientists have released a more detailed version of the first image of a black hole.
That first image, released four years ago, showed a blurry, round-shaped orange object. Now, researchers have used machine learning methods to create an improved picture.
The new image was recently published in the Astrophysical Journal Letters. The same shape remains as in the first image, but it has a narrower ring and sharper resolution.
Scientists have said the black hole in the image sits at the center of a galaxy called M87, more than 53 million light-years from Earth. A light year is the distance light travels in a year --- about 9.5 trillion kilometers. The mass of the black hole is 6.5 billion times greater than that of Earth’s sun.
A network of radio telescopes around the world gathered the data used to make the image. But even with many telescopes working together, holes remained in the data. In the latest study, scientists depended on the same data, but used machine learning methods to fill in the missing information.
The resulting picture looks similar to the image, but with a thinner “doughnut” and a darker center, the researchers said.
“For me, it feels like we’re really seeing it for the first time,” said the lead writer of the study, Lia Medeiros. She is an astrophysicist at the Institute for Advanced Study in New Jersey.
She said it was the first time the team had used machine learning to fill in the data holes.
With a clearer picture, researchers hope to learn more about the black hole’s properties and gravity in future studies. Medeiros said the team also plans to use machine learning on other images of space objects. This could include the black hole at the center of our galaxy, the Milky Way.
The study's four writers are members of the Event Horizon Telescope (EHT) project. It is an international effort begun in 2012 with the goal of directly observing a black hole's nearby environment. A black hole's event horizon is the point beyond which anything - stars, planets, gas, dust and all forms of electromagnetic radiation – can escape.
Dimitrios Psaltis is an astrophysicist at Georgia Institute of Technology in Atlanta, Georgia. He told Reuters news agency the main reason the first image had many gaps is because of where the observing telescopes sit. The telescopes operate from the tops of mountains and “are few and far apart from each other,” Psaltis said.
As a result, the telescope system has a lot of 'holes' and scientists can now use machine learning methods to fill in those gaps, he added. "The image we report in the new paper is the most accurate representation of the black hole image that we can obtain with our globe-wide telescope," Psaltis said.
I’m Bryan Lynn.
The Associated Press and Reuters reported on this story. Bryan Lynn adapted the reports for VOA Learning English.
Words in This Story
machine learning – n. the use of computer systems that are able to learn and adapt without following direct instructions
resolution – n. a measure of the sharpness of an image
galaxy – n. a very large group of stars held together in the universe
doughnut – n. a small. Round, fried cake that usually has a hole in the middle
accurate – adj. true and correct
obtain – v. to get something
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