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[00:00.40] Scientists have released a more detailed version of the first image of a black hole.

[00:09.43] That first image, released four years ago, showed a blurry, round-shaped orange object.

[00:18.46] Now, researchers have used machine learning methods to create an improved picture.

[00:27.23] The new image was recently published in the Astrophysical Journal Letters.

[00:34.66] The same shape remains as in the first image, but it has a narrower ring and sharper resolution.

[00:44.76] 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.

[01:00.16] A light year is the distance light travels in a year --- about 9.5 trillion kilometers.

[01:09.99] The mass of the black hole is 6.5 billion times greater than that of Earth’s sun.

[01:20.09] A network of radio telescopes around the world gathered the data used to make the image.

[01:29.38] But even with many telescopes working together, holes remained in the data.

[01:37.62] In the latest study, scientists depended on the same data, but used machine learning methods to fill in the missing information.

[01:49.32] The resulting picture looks similar to the image, but with a thinner “doughnut” and a darker center, the researchers said.

[02:01.26] “For me, it feels like we’re really seeing it for the first time,” said the lead writer of the study, Lia Medeiros.

[02:12.15] She is an astrophysicist at the Institute for Advanced Study in New Jersey.

[02:19.59] She said it was the first time the team had used machine learning to fill in the data holes.

[02:28.62] With a clearer picture, researchers hope to learn more about the black hole’s properties and gravity in future studies.

[02:47.48] Medeiros said the team also plans to use machine learning on other images of space objects.

[02:48.80] This could include the black hole at the center of our galaxy, the Milky Way.

[02:55.71] The study's four writers are members of the Event Horizon Telescope (EHT) project.

[03:04.74] It is an international effort begun in 2012 with the goal of directly observing a black hole's nearby environment.

[03:15.90] A black hole's event horizon is the point beyond which anything - stars, planets, gas, dust and all forms of electromagnetic radiation – can escape.

[03:30.77] Dimitrios Psaltis is an astrophysicist at Georgia Institute of Technology in Atlanta, Georgia.

[03:40.61] He told Reuters news agency the main reason the first image had many gaps is because of where the observing telescopes sit.

[03:52.82] The telescopes operate from the tops of mountains and “are few and far apart from each other,” Psaltis said.

[04:03.18] 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.

[04:16.72] "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.