Scientists have used artificial intelligence to construct a three-dimensional model of an energetic outburst, or outburst, that occurred around the Milky Way’s central black hole, Sagittarius A* (Sgr A*). This 3D model could help scientists get a clearer picture of the tumultuous environment that forms around supermassive black holes in general.
The material swirling around Sgr A* exists in a flattened structure called an “accretion disk,” which can flare periodically. These bursts occur in a range of light wavelengths, ranging from high-energy X-rays to low-energy infrared light and radio waves.
The supercomputer simulations suggest that an outburst observed by the Atacama Large Millimeter/Submillimeter Array (ALMA) on April 11, 2017 came from two bright spots of dense material in Sgr A*’s accretion disk, both pointed toward Earth. Those bright spots swirl around the supermassive black hole, which has a mass about 4.2 million times that of the Sun, while the distance between Earth and the Sun is about half that. That’s about 47 million miles (75 million kilometers).
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Reconstructing these flares in 3D based on observational data is no easy task. To address this, the team, led by scientist Aviad Levis of the California Institute of Technology, proposed a new imaging technique called ‘orbital polarimetric tomography’. The method is similar to 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 drives highly energetic outbursts known as eruptions, which leave behind observational signatures at X-ray, infrared and radio wavelengths,” Levis told Space.com. “Recently theorists have proposed several mechanisms for the creation of such eruptions, one of which is due to extremely bright, compact areas that suddenly form within the accretion disk.”
The main result of this work, he added, is the recovery of what the 3D structure of the radio luminosity around Sgr A* might look like immediately after a solar flare detection.
Building a black hole from a single pixel
“Sgr A* lies at the heart of our own Milky Way Galaxy, making it the closest supermassive black hole and an excellent candidate for studying such outbursts,” Levis said. “To do that effectively, you still need a bit of luck when ALMA observations coincide with an eruption.”
He explained that on April 11, 2017, ALMA observed Sgr A* immediately after a violent outburst, captured in X-rays. The radio data obtained by ALMA contained a periodic signal that was consistent with what would be expected for an orbit around Sgr A*.
“This prompted our development of a computational approach that could extract the 3D structure from the time series data observed by ALMA,” Levis added. ‘Unlike the 2D image from the Event Horizon Telescope (EHT) of Sgr A*, we were interested in recovering the 3D volume, and to do that we relied on physical modeling of how light travels along curved trajectories within the Earth’s strong gravitational field. a black hole.”
To achieve their results, the scientists looked at the physics derived from Albert Einstein’s 1915 theory of gravity, general relativity, and then applied these concepts surrounding supermassive black holes to a neural network. This network was then used to create the Sgr A* model.
“This work is a unique collaboration between astronomers and computer scientists developing advanced computational tools in both the fields of AI and gravitational physics, each contributing an important part of the whole to this first attempt to reveal the 3D radio emission structure around Sgr A .*,” said Levis. “The result is not a photo in the regular sense; rather, it is a computational 3D image extracted from time series observations by constraining a neural network with the expected physics of how gas orbits and orbits the black hole. how synchrotron radiation is emitted in the black hole process.”
He explained that the team computationally placed 3D “emissions” into orbit around Sgr A*, starting with a random structure. Through ray tracing, which refers to graphical simulations of the physical behavior of light, Levis and colleagues were able to model how ALMA would view the structure around Sgr A* in the future. Those models started 10 minutes after the eruption, then 20 minutes later, 30 minutes later – and so on.
“The technology of neural radiation fields and general relativistic ray tracing gives us a way to change the 3D structure until the model matches the observations,” Levis added.
The team found that this yielded conclusions about the environment around Sgr A* that are indeed predicted by the theory, showing that the brightness is concentrated in several small regions within the accretion disk. Still, certain aspects of this work were surprising to Levis and the rest of the team.
“The biggest surprise was that we were able to figure out the 3D structure from observations of the light curve… essentially a video of a single flickering pixel,” the researcher said. “Think about it: if I told you you could recover a video from just a single pixel, you’d say that sounds practically impossible. The key is that we’re not recovering random video.
“We recover the 3D structure of emission around a black hole, and we can use the expected gravitational and emission physics to constrain our reconstruction.”
Levis added that the fact that ALMA measures not only the intensity of the light, but also its polarization, gave the team a very informative signal with clues about the 3D structure of flares around Sgr A*
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In the future, Levis said he and the team plan to run the simulation while simultaneously changing the parameters of the physics used to constrain the AI.
“These results are an exciting first step, building on the belief that Sgr A* is a black hole whose environment conforms to the prescribed gravity and emission models; the accuracy of our result depends on the validity of these assumptions,” concluded Levis. “In the future, we want to relax these restrictions to allow for deviations from expected physics.
“Our approach, which leverages the synergy between physics and AI, 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.