New York News
In a new paper published in the journal Nature Astronomy, astronomers with Breakthrough Listen Initiative — the largest ever scientific research program aimed at finding evidence of alien civilizations — present a new machine learning-based method that they apply to more than 480 hours of data from the Robert C. Byrd Green Bank Telescope, observing 820 nearby stars. The method analyzed 115 million snippets of data, from which it identified around 3 million signals of interest. The authors then inspected the 20,515 signals and they identified 8 previously undetected signals of interest, although follow-up observations of these targets have not re-detected them.
An artist’s impression of the Robert C. Byrd Green Bank Telescope receiving signals from space. Image credit: Danielle Futselaar / Breakthrough Listen.
“The key issue with any technosignature search is looking through this huge haystack of signals to find the needle that might be a transmission from an alien world,” said Dr. Steve Croft, an astrophysicist at the University of California, Berkeley and a member of the Breakthrough Listen team.
“The vast majority of the signals de