Researchers at Breakthrough Listen, a multimillion-dollar campaign to seek out signals from alien civilizations, still don’t know exactly what’s causing repeated bursts of radio waves from an distant galaxy — but thanks to artificial intelligence, they’re keeping closer tabs on the source, whatever it turns out to be.
A team led by Gerry Zhang, a graduate student at the University of California at Berkeley, developed a new type of machine-learning algorithm to comb through data collected a year ago during an observing campaign that used the Green Bank Telescope in West Virginia.
The campaign focused on a radio source known as FRB 121102, located in a dwarf galaxy sitting 3 billion light-years away in the constellation Auriga. Astronomers have observed plenty of fast radio bursts over the past decade, each lasting only a few milliseconds. Only FRB 121102 has been found to send out repeated bursts, however.
A number of theories have been proposed to explain the bursts, ranging from interactions involving magnetized neutron stars and black holes to deliberate signaling by advanced civilizations.