An international team of astronomers, using a neural network trained on millions of synthetic black hole simulations and data from the Event Horizon Telescope, has uncovered new insights—including that the Milky Way’s central black hole is spinning near its maximum speed—thanks to advanced computational support from the University of Southern California’s Information Sciences Institute.
A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the Event Horizon Telescope, they now predict, among other things, that the black hole at the center of our Milky Way is spinning at near top speed. The astronomers publish their results and methodology in three papers in the journal Astronomy & Astrophysics. The University of Southern California’s Information Sciences Institute (ISI) contributed to the project by providing the Pegasus workflow management system and support for high-throughput data analysis.
In 2019, the Event Horizon Telescope Collaboration released the first image of a supermassive black hole at the center of the galaxy M87. In 2022, they presented the image of the black hole of our Milky Way, Sagittarius A*. However, the data behind the images still contained a wealth of hard-to-crack information. An international team of researchers trained a neural network to extract as much information as possible from the data.
Researchers in the SciTech group at the University of Southern California’s Information Sciences Institute (ISI), part of the Viterbi School of Engineering, provided software, infrastructure access, and facilitation to support the required computations. The NSF-funded Pegasus workflow management system, developed at ISI, was used to orchestrate the computational tasks. High-throughput computing was enabled through the OSG OSPool, in part facilitated by the ISI team.
“It has been a pleasure to support the EHT team in this groundbreaking work. It’s a strong example of how Pegasus and the OSG OSPool can enable large-scale, data-intensive science.” said Mats Rynge, Senior Computer Scientist in the SciTech group.
The broader ecosystem of coordinated computational services also included CyVerse for data storage, the Max Planck Computing and Data Facility in Germany for neural network training, and key software tools such as TensorFlow, Horovod, and CASA.
From a handful to millions
Previous studies by the Event Horizon Telescope Collaboration used only a handful of realistic synthetic data files. This time, the astronomers fed millions of such data files into a so-called Bayesian neural network that can quantify uncertainties. This allowed the researchers to make a much better comparison between the EHT data and the models.
Thanks to the neural network, the researchers now suspect, for example, that the black hole at the center of the Milky Way is spinning almost at top speed. Its rotation axis points to the Earth. In addition, the emission near the black hole is mainly caused by extremely hot electrons in the surrounding accretion disk and not by a so-called jet. Also, the magnetic fields in the accretion disk seem to behave differently than the usual theories of such disks.
“That we are defying the prevailing theory is of course exciting,” says lead researcher Michael Janssen (Radboud University Nijmegen, the Netherlands). “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. And when the Africa Millimetre Telescope, which is under construction, joins in with data collection, we will get even better information to validate the general theory of relativity for supermassive compact objects with a high precision.”
The researchers did not just make predictions about Sagittarius A*. They also looked at M87*, the black hole at the center of M87. Among other things, they found that this black hole is also spinning fast, but not as fast as Sagittarius A*. Besides that, it is spinning in the opposite direction to the infalling gas. The astronomers suggest that this counter-rotating motion may be the result of a merger with another galaxy.
Scientific papers
Deep learning inference with the Event Horizon Telescope I. Calibration improvements and a comprehensive synthetic data library. By: M. Janssen et al. In: Astronomy & Astrophysics, 6 June 2025. [original (open access) | preprint (pdf) ]
Deep learning inference with the Event Horizon Telescope II. The Zingularity framework for Bayesian artificial neural networks. By: M. Janssen et al. In: Astronomy & Astrophysics, 6 June 2025. [original (open access) | preprint (pdf)]
Deep learning inference with the Event Horizon Telescope III. Zingularity results from the 2017 observations and predictions for future array expansions. By: M. Janssen et al. In: Astronomy & Astrophysics, 6 June 2025. [original (open access) | preprint (pdf)]
About USC Information Sciences Institute (ISI)
Founded in 1972, USC Information Sciences Institute is a world leader in research and development of advanced information processing, computer and communications technologies. ISI is known for creating the Domain Name System (DNS). ISI has made major contributions to artificial intelligence, networking and cybersecurity, computational systems and technology, and informatics systems research, as well as space, quantum computing, and more. ISI also runs the MOSIS Service that enables universities, government agencies, research institutes and businesses to prototype chips efficiently and cost-effectively. With its center in Los Angeles’ Silicon Beach in California and branches in Arlington, VA, and Boston, MA, ISI is one of the nation’s largest – and most successful – university computer research institutes. ISI is a unit of the University of Southern California’s Viterbi School of Engineering, which is consistently ranked in the top 10 graduate programs (U.S. News and World Report).
Link to story on ISI Research News.
About NOVA
The Netherlands Research School for Astronomy (NOVA, www.astronomie.nl) is the alliance of the astronomical institutes of the universities of Amsterdam, Groningen, Leiden, and Nijmegen. The mission of Top Research School NOVA is to carry out frontline astronomical research in the Netherlands, to train young astronomers at the highest international level, and to share its new discoveries with society. The NOVA laboratories are specialized in building state-of-the-art optical/infrared and submillimeter instrumentation for the largest telescopes on earth.
Contacts
Michael Janssen
Department of Astrophysics, Institute for Mathematics, Astrophysics and Particle Physics, Radboud University, Nijmegen, the Netherlands
M.Janssen@astro.ru.nl
https://www.ru.nl/en/people/janssen-m-michael
Ewa Deelman
Information Sciences Institute, University of Southern California, California, USA
deelman@isi.edu
https://isi.edu
Chi-kwan Chan
Steward Observatory and Department of Astronomy, University of Arizona, Tucson, Arizona, USA
chanc@arizona.edu
https://astro.arizona.edu/person/chi-kwan-ck-chan
Jordy Davelaar
Department of Astrophysical Sciences, Princeton University, Princeton, New Jersey, USA
jdavelaar@princeton.edu
https://web.astro.princeton.edu/people/jordy-davelaar
https://jordydavelaar.com
Maciek Wielgus
Instituto de Astrofísica de Andalucía-CSIC, Granada, Spain
mwielgus@iaa.es
https://maciekwielgus.wixsite.com/maciek