Scientists used artificial intelligence to create a three-dimensional model of an energetic explosion, or flare, occurring around the Milky Way’s central black hole, Sagittarius A* (Sgr A*). This 3D model could help scientists develop a clearer picture of the turbulent environment that generally forms around supermassive black holes.
The material orbiting Sgr A* is found in a flattened structure called an “accretion disk” that may flare periodically. These flashes occur in a variety of wavelengths of light, from high-energy X-rays to low-energy infrared light and radio waves.
Supercomputer simulations suggest that a flare seen by the Atacama Large Millimeter/Submillimeter Array (ALMA) on April 11, 2017 was caused by two bright points of dense matter in Sgr A*’s accretion disk, both facing Earth. These bright spots orbit the supermassive black hole, which is about 4.2 million times the mass of the Sun and is about half the distance between the Earth and the Sun. That’s about 47 million miles (75 million kilometers).
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Reconstructing these flares in 3D from observational data is no easy task. To overcome this problem, the team led by California Institute of Technology scientist Aviad Levis proposed a new imaging technique called “orbital polarimetric tomography.” The method is no different from medical computed tomography, or CT scans, performed in hospitals around the world.
“The compact region around the galactic center is an extreme place where hot, magnetized gas orbits a supermassive black hole at relativistic speeds [speeds approaching that of light]. This unique environment powers high-energy bursts known as flares that leave observational signatures at X-ray, infrared and radio wavelengths,” Levis told Space.com. “Recently, theorists have proposed various mechanisms for the emergence of such flares. they suggested; one of them: through extremely bright, compact regions that suddenly form in the accretion disk.”
He added that the main result of this work was the recovery of what the 3D structure of the radio luminosity around Sgr A* might look like immediately after detection of a flare.
Creating a black hole from a single pixel
“Sgr A* is located at the heart of our Milky Way galaxy, making it the closest supermassive black hole and a prime candidate for studying such flares,” Levis said. said. “To do this effectively, you still need an element of luck when ALMA observations coincide with a flare.”
He announced that on April 11, 2017, ALMA observed Sgr A* immediately following a violent explosion captured in X-rays. Radio data obtained by ALMA had a periodic signal consistent with what would be expected for an orbit around Sgr A*.
“This led us to develop a computational approach that could extract 3D structure from the time series data observed by ALMA,” Levis added. “Unlike the Event Horizon Telescope (EHT) 2D image of Sgr A*, we were interested in recovering 3D volume, and to do this we relied on physical modeling of how light travels along curved orbits within the strong gravitational field of a black hole.”
To reach their conclusions, scientists looked at physics derived from Albert Einstein’s 1915 theory of gravity (general relativity) and then applied these concepts to a neural network around supermassive black holes. This network was then used to create the Sgr A* model.
“This work is a unique collaboration between astronomers and computer scientists developing cutting-edge computational tools from both the fields of artificial intelligence and gravitational physics, each contributing an important part of the whole in this first attempt to reveal the 3D radio emission structure around Sgr A. *” said Levis. “The result is not a photograph in the normal sense; rather, it is a computational 3D image obtained from time-series observations by constraining a neural network to the expected physics of how gas orbits around the black hole and how synchrotron radiation propagates inside the black hole process.”
He explained that the team computationally fitted 3D “emissions” into orbit around Sgr A*, starting from a random structure. Through ray tracing, which refers to graphical simulations of the physical behavior of light, Levis and his colleagues were able to model how ALMA would see structure around Sgr A* in future times. These patterns started 10 minutes after the flare, then 20 minutes later, 30 minutes later, etc.
“Neural luminance fields and general relativistic ray tracing technology give us a way to start modifying the 3D structure until the model matches the observations,” Levis said. he added.
The team found that this yielded results about the environment around Sgr A* showing that the brightness predicted by theory is concentrated in a few small regions within the accretion disk. Still, some aspects of this work were surprising to Levis and the rest of the team.
“The biggest surprise was that we were able to recover the 3D structure from the light curve observations…essentially a video of a single flickering pixel,” the researcher said. “Think about it: If I told you that you could recover a video from a single pixel, you would say that it is practically impossible. The important thing is that we are not recovering a random video.
“We recover the 3D structure of the emission around a black hole and can use the expected physics of gravity and emission to constrain our reconstruction.”
Levis added that the fact that ALMA measured not only the intensity of the light but also its polarization gave the team a highly informative signal that contained clues about the 3D structure of the flares around Sgr A*.
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Going forward, Levis said he and his team plan to run the simulation while varying the physics parameters used to constrain the AI.
“These results are an exciting first step based on the belief that Sgr A* is a black hole whose environment obeys established gravitational and emission patterns; the accuracy of our result depends on the validity of these assumptions,” Levis said. “In the future, we would like to relax these restrictions to allow for deviations from expected physics.
“By leveraging the synergy between physics and artificial intelligence, our approach opens the door to new and exciting questions whose answers will continue to advance our understanding of black holes and the universe.”
The team’s research was published Monday (April 22) in the journal Nature Astronomy.