Researchers at the University of Maryland have identified what appears to be the first known dormant supermassive black hole located at a substantial distance from the center of its host galaxy. The black hole, which sits approximately 30,000 light-years from the galactic core, was detected only when it disrupted a passing star, creating a detectable burst of light. This discovery challenges the long-held assumption that supermassive black holes primarily reside at galactic centers.
Scientists have theorized for years that galactic collisions and mergers could displace black holes to the outer regions of galaxies, yet finding such “wandering” objects has proven extremely difficult since inactive black holes produce no detectable light. The University of Maryland team overcame this challenge by developing an artificial intelligence system trained to recognize the distinctive light signatures produced during tidal disruption events, which occur when a star ventures close enough to a black hole to be torn apart by gravitational forces. The team deployed this AI program in August 2025, and within three months it had identified the event leading to the black hole’s discovery.
The black hole’s mass is comparable to that of Sagittarius A*, the supermassive black hole at the center of the Milky Way. Researchers note that the object’s apparent lack of a surrounding galaxy is particularly puzzling and likely results from a galactic collision in the distant past. One explanation involves a larger galaxy absorbing a smaller companion and gradually stripping away most of its stars, leaving only the dense core and black hole. An alternative scenario involves a chaotic three-body interaction among multiple black holes that could have ejected the wandering black hole from a galactic center.
The findings, published in The Astrophysical Journal Letters, suggest that dormant wandering black holes may be far more common than previously recognized. Researchers expect that upcoming sky surveys using advanced facilities such as the Vera C. Rubin Observatory will identify dozens or possibly hundreds of such objects annually. The discovery demonstrates that machine learning combined with conventional sky surveys offers a cost-effective approach to identifying these previously elusive astronomical objects and may open new avenues for understanding galactic formation and evolution.
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