Artificial intelligence helps track down mysterious cosmic radio bursts

phys.org | 9/10/2018 | Staff
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Artificial intelligence is invading many fields, most recently astronomy and the search for intelligent life in the universe, or SETI.

Researchers at Breakthrough Listen, a SETI project led by the University of California, Berkeley, have now used machine learning to discover 72 new fast radio bursts from a mysterious source some 3 billion light years from Earth.

Fast - Radio - Bursts - Pulses - Radio

Fast radio bursts are bright pulses of radio emission mere milliseconds in duration, thought to originate from distant galaxies. The source of these emissions is still unclear, however. Theories range from highly magnetized neutron stars blasted by gas streams from a nearby supermassive black hole, to suggestions that the burst properties are consistent with signatures of technology developed by an advanced civilization.

"This work is exciting not just because it helps us understand the dynamic behavior of fast radio bursts in more detail, but also because of the promise it shows for using machine learning to detect signals missed by classical algorithms," said Andrew Siemion, director of the Berkeley SETI Research Center and principal investigator for Breakthrough Listen, the initiative to find signs of intelligent life in the universe.

Breakthrough - Listen - Algorithm - Kinds - Signals

Breakthrough Listen is also applying the successful machine-learning algorithm to find new kinds of signals that could be coming from extraterrestrial civilizations.

While most fast radio bursts are one-offs, the source here, FRB 121102, is unique in emitting repeated bursts. This behavior has drawn the attention of many astronomers hoping to pin down the cause and the extreme physics involved in fast radio bursts.

AI - Algorithms - Radio - Signals - Data

The AI algorithms dredged up the radio signals from data were recorded over a five-hour period on Aug. 26, 2017, by the Green Bank Telescope in West Virginia. An earlier analysis of the 400 terabytes of data employed standard computer algorithms to identify 21 bursts during that period. All were seen within one hour,...
(Excerpt) Read more at: phys.org
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