When two neutron stars collide, they…

When two neutron stars collide, they generate gravitational waves and light across the electromagnetic spectrum, from intense gamma ray flashes to faint radio signals that can persist for years.

These multi-messenger events contain rich information about the physics of compact objects, their environments and the formation of heavy elements, but extracting that information efficiently has proved challenging.

A collaboration led by researchers at the U.S. Department of Energy's Argonne National Laboratory, working with Johns Hopkins University, the University of Chicago and the University of Illinois Urbana-Champaign, has developed a new AI-powered framework to tackle this problem.

The system, called RADAR, for Radio Afterglow Detection and AI-driven Response, is designed to combine gravitational wave data with radio observations in a coordinated, resource-aware way. One of RADAR's distinctive features is its use of AI to read the human-generated messages that astronomers rely on to share results from telescopes around the globe. By automatically parsing these notices, the system can keep track of evolving observations and adjust follow-up plans dynamically.