Scientists used artificial intelligence to construct a three-dimensional model of energy bursts or flares that occur around the black hole Sagittarius A* (Sgr A*) at the center of the Milky Way. This 3D model can help scientists gain a clearer understanding of the chaotic environment that forms around supermassive black holes.
The material swirling around Sgr A* exists in a flat structure called an “accretion disk,” which can periodically flare. These flares occur in a range of light wavelengths, from high-energy X-rays to low-energy infrared light and radio waves.
Supercomputer simulations show that the flare seen by the Atacama Large Millimeter/submillimeter Array (ALMA) on April 11, 2017, originated from two bright spots of dense material in the Sagittarius A* accretion disk, both facing Earth. The bright spots orbit a supermassive black hole, which is about 4.2 million times the mass of the Sun, at a distance about half the distance between Earth and the Sun. This is approximately 47 million miles (75 million kilometers).
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Reconstructing these flares in 3D from observational data is no easy task. To solve this problem, a team led by Caltech scientist Aviad Levis proposed a new imaging technique called “orbital polarization tomography.” This method is no different from medical computed tomography (CT) scans performed in hospitals around the world.
“The dense region around the center of the Milky Way is an extreme place where hot, magnetized gas orbits supermassive black holes at relativistic speeds. [speeds approaching that of light]. This unique environment powers high-energy eruptions called flares, which leave observational signatures in X-ray, infrared and radio wavelengths,” Levis told Space.com. “Recently, theorists have proposed several mechanisms for the occurrence of such flares, one of which involves passing through an extremely bright, compact region that suddenly forms within an accretion disk.
He added that a key result of this work is what the 3D structure of the radioluminescence surrounding Sgr A* might look like immediately after a flare detection.
Building a black hole from a single pixel
“Sagittarius A* is located at the center of our galaxy, making it the closest supermassive black hole and a prime candidate for studying such flares,” Levis said. “To do this effectively, you still need luck when the ALMA observations coincide with the flare.”
He explained that ALMA observed the violent eruption of Sagittarius A* immediately after X-rays captured it on April 11, 2017. The radio data acquired by ALMA have periodic signals consistent with those expected from the orbit around Sgr A*.
“This led us to develop a computational method that can extract 3D structure from the time series data observed by ALMA,” Levis added. “In contrast to the Event Horizon Telescope (EHT) 2D images of Sagittarius A*, we are interested in recovering the 3D volume, and to do this we rely on a physical model of how light propagates along a curved trajectory in a strong gravitational field. A black hole. “
To achieve their results, the scientists looked at physics derived from Albert Einstein’s 1915 theory of gravity and general relativity, then applied these concepts surrounding supermassive black holes to neural networks. This network is then used to build a Sgr A* model.
“This work is a unique collaboration between astronomers and computer scientists, advancing cutting-edge computational tools in artificial intelligence and gravitational physics, each of which contributes to the overall effort in the first attempt to reveal the 3D radio emission structure around Sgr A. “The result is not a photograph in the conventional sense; rather, it is a computational 3D image extracted from a time series of observations, using expectations of how gas orbits the black hole and how synchrotron radiation is emitted in the black hole. Physics to constrain neural network processes.
He explained that the team computationally placed 3D “shots” in orbit around Sgr A*, starting from arbitrary structures. Using ray tracing, a graphical simulation of the physical behavior of light, Levis and colleagues were able to simulate how ALMA would see the structure around Sgr A* in the future. The models start 10 minutes after the flare, then 20 minutes later, 30 minutes later – and so on.
“Neural radiation fields and general relativistic ray tracing techniques give us a way to start changing the 3D structure until the model matches the observations,” Levis added.
The team found that this led to conclusions about Sgr A*’s surroundings that were indeed predicted by theory, showing that the brightness was concentrated in several small regions within the accretion disk. Still, some aspects of the work surprised Levi and the rest of the team.
“The biggest surprise was that we were able to recover the 3D structure from light curve observations… essentially videos of individual blinking pixels,” the researchers said. “Think about it: if I told you that you could recover a video from just one pixel, you would say that sounds almost impossible. The point is that we are not recovering arbitrary video.
“We are recovering the 3D structure of the emission around the black hole, and we can use the expected gravity and emission physics to constrain our reconstruction.”
Levis added that the fact that ALMA not only measures the intensity but also the polarization of the light provides the team with an informative signal that contains clues about the 3D structure of the flare around Sgr A*.
Going forward, Levis said he and his team plan to run simulations while varying the physical parameters used to constrain the artificial intelligence.
“These results are an exciting first step, relying on the belief that Sagittarius A* is a black hole and that its environment follows a prescribed model of gravity and emission; the accuracy of our results depends on the validity of these assumptions,” concluded Levis . “In the future, we hope to relax these constraints to allow for deviations from expected physical phenomena.
“Our approach exploits synergies between physics and artificial intelligence, opening the door to new and exciting questions whose answers will continue to advance our understanding of black holes and the universe.”
The team’s findings were published in the journal Nature Astronomy on Monday (April 22).
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