by Scientists used artificial intelligence to build a three-dimensional model of an energetic spark, or flare, that occurred around the Milky Way’s central black hole, Sagittarius A* (Sgr A*). This 3D model could help scientists develop a clearer picture of the chaotic environment that forms around supermassive black holes in general.
The material swirling around Sgr A* exists in a flattened structure called an “accretion disk” that can flare up from time to time. These flares occur over a range of wavelengths of light, all the way from high-energy X-rays to low-energy infrared light and radio waves.
The supercomputer simulations suggest that a flare seen by the Atacama Large Millimeter/Submillimeter Array (ALMA) on April 11, 2017 was coming from two bright spots of dense material in the accretion disk of Sgr A*, both of which was in front of the Universe. Those bright spots orbit the supermassive black hole, which has a mass of about 4.2 million times that of the sun, and is separated by about half the distance between 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 a daunting task. To combat this, the team, led by California Institute of Technology scientist Aviad Levis, proposed a new imaging technique called “orbital polarimetric tomography.” This method is not unlike medical computed tomography, or CT scanning, which is performed in hospitals around the globe.
“The dense region around the Galactic center is a very large place where hot magnetized gas orbits a supermassive black hole at relativistic speeds. [speeds approaching that of light]. This unique environment powers highly energetic eruptions called flares, which leave observable signatures at X-ray, infrared and radio wavelengths,” Levis told Space.com. through extremely bright, dense regions that suddenly form within of the add-on disk.”
The main result of this work, he said, is to recover what the 3D structure of the radio brightness around Sgr A* might look like directly after the detection of flares.
Construct a black hole from a single pixel
“Sgr A* is located at the heart of our own Milky Way galaxy, making it the closest supermassive black hole and a prime candidate for studying such flares,” Levis said. “To do that effectively, you still need an element of luck when the ALMA observations coincide with a flare.”
He explained that on April 11, 2017, ALMA was observing Sarcel A* directly after a violent eruption captured in X-rays. The radio data obtained by ALMA had a periodic signal consistent with what would be expected for an orbit around Sgr A*.
“This motivated us to develop a computational approach that could extract the 3D structure from the time series data seen by ALMA,” Levis added. “In contrast to the 2D Event Horizon Telescope (EHT) image of Sgr A*, we were interested in recovering the 3D volume, and to do so, we relied on physical modeling of how light travels along curved paths within it strong gravitational field of. black hole.”
To reach their findings, the scientists looked at the physics derived from Albert Einstein’s 1915 theory of gravity, general relativity, then applied those concepts to supermassive black holes on 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 who advance cutting-edge computational tools from both the fields of AI and gravitational physics, each contributing an important part of the whole to this first attempt at a 3D radio emission structure around Disclosure of A score. *,” said Levis. “The result is not a photograph in the usual sense; rather, it is a 3D computational image extracted from time-series observations by constraining a neural network to the expected physics of how gas orbits the black hole and how synchrotron radiation is emitted in the process.”
He explained that the team computationally placed 3D “emissions” in orbit around an A* Score, starting with an arbitrary 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 the structure around Sgr A* in the future. Those models started 10 minutes after the flare, then 20 minutes later, 30 minutes later – and so on.
“The technology of neural radiance 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 led to conclusions about the environment around Sgr A* that are indeed predicted by theory, showing that brightness is concentrated in a few small regions within the accretion disk. Still, aspects of this work surprised Levis and the rest of the team.
“The biggest surprise was that we were able to recover the 3D structure from light curve observations… basically a video of a single flickering pixel,” said the researcher. “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 key is that we are not recovering an arbitrary video.
“We are retrieving the 3D structure of the emission around a black hole, and we can leverage 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 the flares around Sgr A*.
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Going forward, Levis said he and the team plan to run the simulation while changing the physics parameters used to constrain the AI.
“These results are an exciting first step, which depends on the belief that Sgr A* is a black hole whose environment conforms to established gravitational and emission models; the accuracy of our results depends on the validity of these assumptions,” a Levis concluded. “Going forward, we want to loosen these constraints to allow deviations from the expected physics.
“Our approach, which takes advantage of the synergy between physics and AI, opens the door to exciting new questions whose answers will continue to advance our understanding of black holes and the universe.”
The team’s research was published on Monday (April 22) in the journal Nature Astronomy.
