AI Reveals Fast-Spinning Milky Way Black Hole
- Astronomers using artificial intelligence have discovered that Sagittarius A*, teh supermassive black hole at the Milky Way's center, is spinning at close to it's maximum possible speed.
- The international team trained a neural network using data generated by the Center for High Throughput Computing (CHTC) at the University of Wisconsin-Madison.This allowed them to analyze data...
- miron Livny,director of the CHTC,noted the project's reliance on high-throughput computing,a method he pioneered.
AI unveils the supermassive black hole at the heart of the Milky Way is spinning at nearly the speed of light, challenging existing theories. This groundbreaking discovery,powered by artificial intelligence and high-throughput computing,analyzed data from the Event Horizon Telescope. Scientists used millions of simulations to understand the behavior of Sagittarius A*. The research, led by an international team, indicates emissions originate from hot electrons in the accretion disk. This innovative approach highlights the importance of reliable workflow automation. The team’s findings offer fresh perspectives on black hole dynamics. News Directory 3 reported on the use of massive computing power and the innovative methodology. Now, researchers plan to refine their models. Discover what’s next as they further explore the mysteries of black holes.
Milky Way’s Black Hole Spinning Near Light Speed, AI Reveals
Updated June 15, 2025
Astronomers using artificial intelligence have discovered that Sagittarius A*, teh supermassive black hole at the Milky Way’s center, is spinning at close to it’s maximum possible speed. The findings, gleaned from millions of synthetic simulations, offer new insights into black hole behavior and challenge existing models.
The international team trained a neural network using data generated by the Center for High Throughput Computing (CHTC) at the University of Wisconsin-Madison.This allowed them to analyze data from the Event Horizon Telescope (EHT), which previously captured the first images of Sagittarius A* and the black hole in galaxy M87.
miron Livny,director of the CHTC,noted the project’s reliance on high-throughput computing,a method he pioneered. This approach distributes computing tasks across numerous computers, transforming a complex problem into smaller, manageable ones. The NSF-funded Open Science Pool, managed by the Partnership to Advance Throughput Computing (PATh), provided the computing power, utilizing resources from over 80 institutions.
The AI analysis suggests the black hole’s rotation axis points toward Earth. furthermore, the emission near the black hole appears to originate primarily from hot electrons in the accretion disk, rather than a jet. The magnetic fields within the disk also seem to deviate from conventional theories.
“That we are defying the prevailing theory is of course exciting,” said Michael Janssen, lead researcher at Radboud University Nijmegen. “However, I see our AI and machine learning approach primarily as a first step. Next,we will improve and extend the associated models and simulations.”
Chi-kwan Chan, an associate astronomer at the University of arizona’s Steward Observatory, emphasized the importance of scaling to millions of synthetic data files. He cited the need for reliable workflow automation and efficient workload distribution.
What’s next
Researchers plan to refine their models and simulations to further explore the behavior of black holes and their surrounding environments.The team published their methodology and results in three papers in the journal Astronomy & Astrophysics.