A team led by the University of California, Santa Cruz has identified a rare stellar explosion involving a black hole and a massive star. The event, named SN 2023zkd, was detected in July 2023 using an artificial intelligence algorithm developed to scan for unusual cosmic explosions in real time. This early detection enabled astronomers to quickly begin follow-up observations.
The discovery involved telescopes at the Haleakalāa Observatory in Hawaiʻi as part of the Young Supernova Experiment (YSE), which is managed by UC Santa Cruz. YSE surveys about 4% of the night sky every three days and has found thousands of new cosmic events, including dozens within hours or days after their occurrence.
“Something exactly like this supernova has not been seen before, so it might be very rare,” said Ryan Foley, associate professor of astronomy and astrophysics at UC Santa Cruz. “Humans are reasonably good at finding things that ‘aren’t like the others,’ but the algorithm can flag things earlier than a human may notice. This is critical for these time-sensitive observations.”
Researchers believe that SN 2023zkd resulted from a collision between a massive star and its black hole companion as their orbit decayed over time. Their findings were published on August 13 in the Astrophysical Journal. “Our analysis shows that the blast was sparked by a catastrophic encounter with a black hole companion, and is the strongest evidence to date that such close interactions can actually detonate a star,” said lead author Alexander Gagliano, fellow at the NSF Institute for Artificial Intelligence and Fundamental Interactions.
An alternative explanation considered by scientists is that the black hole completely tore apart the star before it could explode independently. In both scenarios described by researchers, only one heavier black hole remains after the event.
SN 2023zkd is located approximately 730 million light-years from Earth. While it initially appeared as an ordinary supernova with one burst of light, further monitoring revealed an unexpected second brightening months later. Archival data indicated that this system had been gradually increasing in brightness for more than four years prior to exploding—an uncommon pattern among supernovae.
Analysis performed partly at UC Santa Cruz showed that material shed by the dying star shaped how its light evolved after explosion. The initial brightening was caused when shockwaves hit low-density gas; later peaks came from collisions with denser material arranged in a disk-like cloud around the system.
Foley explained his collaboration with Gagliano on interpreting spectral data: “Our team also built the software platform that we use to consolidate data and manage observations. The AI tools used for this study are integrated into this software ecosystem,” Foley said. “Similarly, our research collaboration brings together the variety of expertise necessary to make these discoveries.”
Enrico Ramirez-Ruiz, professor of astronomy and astrophysics at UC Santa Cruz, led theoretical work on this project while V. Ashley Villar from Harvard contributed AI expertise. The research group included members from institutions such as Center for Astrophysics | Harvard & Smithsonian and Massachusetts Institute of Technology as part of YSE.
Funding sources included grants from agencies such as National Science Foundation (NSF), NASA, Moore Foundation, and Packard Foundation.
However, Foley noted challenges regarding future funding: “The uncertainty means we are shrinking,” he said, “reducing the number of students who are admitted to our graduate program—many of them being forced out of the field or to take jobs outside the U.S.”
He added that while predicting how AI will be used next remains difficult: “You can easily imagine similar techniques being used to screen for diseases, focus attention for terrorist attacks, treat mental health issues early, and detect financial fraud,” he explained. “Anywhere real-time detection of anomalies could be useful, these techniques will likely eventually play a role.”
