Artificial intelligence opens the secrets of black holes

It may not However, telescopes are able to open all the secrets of super black holes, but artificial intelligence is now in the case. Recently, an international team of astronomers has successfully trained a nervous network with millions of black hole simulation to allow them to explain the mysterious data taken from these mysterious space objects in real life.

Among the different ways to investigate a black hole, the horizon telescope is the most famous event. EHT is not one tool but a number of radio telescopes around the world that works together like a single telescope. Thanks to the EHT, it was possible to get pictures of the super black holes M87 and Sagittarius A*. These are not pictures of the traditional sense, but instead perceptions of radio waves coming from black holes.

To create these photos, giant computers in different parts of the world processing radio signals taken by EHT. But in this process, they ignored many of the information collected, as it was difficult to explain. The new nervous network, coached by experts at the Morgridge Research Institute in Wisconsin, aims to take advantage of this sea from data to improve the solution of EHT readings and new discoveries.

According to a press release issued by the institute, artificial intelligence analyzed the information that was once released and established new standards from the bow*, which is located in the middle of the Milky Way. An alternative image of the black hole structure has been created, with this detection of some new characteristics of the black hole.

“The researchers at the Milky Way Center are almost at a top speed,” the researchers wrote at A. press release. The new image also indicates that the axis of the black hole rotation refers to the ground and gives evidence of the causes and characteristics of the material tablets that revolve around the black hole.

Astronomers had previously estimated that the Sagittarius A* rotates at a moderate speed to a quick speed. It is important to know the actual rotation speed, because it allows us to infer how the radiation surrounding the black hole disposes and provides evidence about its stability.

“We are challenging the prevailing theory, of course,” said lead researcher Michael Yansen of Radbod University in the Netherlands. “However, I see our approach to artificial intelligence and machine learning primarily a first step. After that, we will improve and present the associated models and simulations.”

This story was originally appeared on Wireless In Spanish It was translated from Spanish.