AI uncovers seven rare quasar lens candidates for supermassive black hole studies

Astronomers employed a machine‑learning system to examine more than 800,000 quasar spectra from the Dark Energy Spectroscopic Instrument (DESI). The AI, trained on simulated examples, narrowed the list to about 200 promising objects, which were then manually inspected, resulting in the identification of seven new quasar‑lens candidates. These systems, in which a foreground galaxy’s gravity magnifies a background galaxy, double the number of such lenses found by similar surveys and provide a new tool for measuring the mass of distant galaxies and probing the growth of supermassive black holes.

The discovery was led by Everett McArthur, a graduate student at The Ohio State University, and involved an international collaboration that also includes researchers from the University of Oxford and the Max Planck Institute for Gravitational Physics. The team plans follow‑up observations to confirm the candidates and explore their potential for studying galaxy evolution and black‑hole formation.