VOA科学技术2023 科学家发布首张黑洞图片的高清版

（单词翻译）

Scientists have released a more detailed¹ version of the first image of a black hole.

科学家发布了首张黑洞图片的一个更清晰版本。

That first image, released four years ago, showed a blurry², round-shaped orange object. Now, researchers have used machine learning methods to create an improved picture.

4年前发布的首张黑洞图片显示了一个模糊的橙色圆形物体。现在，研究人员利用机器学习方法生成了一张改进的图片。

The new image was recently published in the Astrophysical Journal Letters. The same shape remains³ as in the first image, but it has a narrower ring and sharper resolution.

这张新图片最近发表在《天体物理学报快报》上。它的形状与第一张图片相同，但是它的圆环更小，分辨率更清晰。

Scientists have said the black hole in the image sits at the center of a galaxy⁴ 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.

科学家表示，图片中的黑洞位于M87星系的中心位置，距离地球超过5300万光年。一光年是光在一年中传播的距离，大约为9.5万亿公里。这个黑洞的质量是太阳质量的65亿倍。

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.

世界各地的射电望远镜网络收集了用于生成该图像的数据。但是，即使许多望远镜协同工作，这些数据依然存在漏洞。在这项最新的研究中，科学家依赖相同的数据，但是利用机器学习方法来填补缺失的信息。

The resulting picture looks similar to the image, but with a thinner "doughnut" and a darker center, the researchers said.

研究人员表示，由此生产的图片与原来的图像相似，但是“圆环”更薄，中心区域更黑暗。

"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 Jersey⁵.

该研究的主要作者莉亚·梅德罗斯表示：“我感觉这是我们第一次目睹它的真颜。”她是新泽西州高等研究所的天体物理学家。

She said it was the first time the team had used machine learning to fill in the data holes.

她说，这是该团队首次利用机器学习来填补数据漏洞。

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 Milky⁶ Way.

有了更清晰的图片，研究人员希望在未来的研究中更多的了解黑洞的性质和引力。梅德罗斯表示，该团队还计划把机器学习用在其它空间物体的图片上。这可能包括银河系中心的黑洞。

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.

这项研究的四位作者是事件视界望远镜项目的成员。这是一项始于2012年的国际努力，目的是直接观测黑洞附近的环境。黑洞的事件视界是任何东西，包括恒星、行星、气体、尘埃和所有形式电离辐射都无法逃离的点。

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.

迪米特里奥斯·普萨尔蒂斯是佐治亚州亚特兰大市佐治亚理工学院的天体物理学家。他对路透社表示，第一张图片有很多间隙的主要原因是由于观测望远镜的位置。普萨尔蒂斯表示，这些望远镜在山顶运行，“数量很少，并且彼此相聚太远。”

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.

他还表示，因此，望远镜系统有很多“漏洞”，科学家现在可以利用机器学习方法来填补这些空白。普萨尔蒂斯说：“我们在新论文中报告的图片是我们用全球望远镜所能获得的黑洞图像的最准确表示。”