AI program detects dozens of ‘alien’ signals from far off galaxy

Green Bank is part of the US Radio Quiet Zone where wireless telecommunications signals are banned to prevent transmissions interfering with a number of radio telescopes

Image The mysterious signals were found in data collected by the Green Bank Telescope in the US

The signals they spotted - fast radio bursts (FRBs) - are bright and quick pulses which were first discovered in 2007 and are believed to come from distant galaxies, although it is not yet know what causes them.

The FRBs are coming from the only known source that has sent out repeating messages, with the rest of the blasts only ever being detected once.

Researchers have used machine learning to discover 72 new fast radio bursts from a mysterious source some 3 billion light years from Earth.

Theories about the origins of FRBs range from waves travelling through magnetised nebulae or past supermassive black holes, to mysterious dark matter or even alien technologies. Researchers were not able to determine that before because they couldn't identify enough hits in a short enough amount of time to determine whether there was a pattern, but with enough positive results in the sample data, they were able to make that determination.

Gerry Zhang stated, "Whether or not FRBs themselves eventually turn out to be signatures of extraterrestrial technology, Breakthrough Listen is helping to push the frontiers of a new and rapidly growing area of our understanding of the Universe around us".

Fast radio bursts are enigmatic radio signals from space that are hard to detect and source. "All were viewed within one hour, suggesting that the source alternates between sessions of quiescence and frenzied process", acknowledged Berkeley postdoctoral researcher Vishal Gajjar.

Knowing that human observations aren't always flawless, UC Berkeley Ph.D. student Gerry Zhang created a machine learning algorithm to apply to the dataset, hoping to pick up any FRBs that the researchers might have missed.

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While FRBs for the most part have been recorded with just one outburst, FRB 121102 is the only one, known till now to repeat bursts.

The SETI Institute has been using IBM Cloud and AI algorithms to analyze over 20 million signals captured by the ATA radio telescopes, using the power of machine learning to greatly improve how anomalous signals of interest can be identified and flagged for further examination.

But Breakthrough Listen, a SETI (search for extraterrestrial intelligence) project led by the University of California, Berkeley, hopes AI can help clarify.

There are a great many mysteries still to unravel in the cosmos, and we may be one step closer to solving one of them thanks to machine learning. This brings the total number of detected bursts from FRB 121102 to around 300 since its discovery.

"This work is only the beginning of using these powerful methods to find radio transients", said Gerry Zhang, doctoral student at the varsity.

Breakthrough Listen is also applying the successful machine learning algorithm to find new kinds of signals that could be emerging from an extraterrestrial civilization. It seems like the pulses are not fired all that regularly after all, at least not if the pattern is longer than 10 milliseconds.

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