By using a new machine learning-operated algorithm, a team of scientists from the University of Toronto has recently detected eight new radio signals originating from five stars located 30 to 90 lightyears away. While there is no evidence yet that these signals might come from extraterrestrial lifeforms, the experts argue that the possibility that other advanced civilizations might use them as “technosignatures” to communicate with us should not be excluded.
The researchers developed a deep-learning algorithm to organize data from telescopes by weeding out human-made interferences to allow astronomers to focus on real patterns coming from distant areas in the universe and then look for patterns which could provide evidence that such signals could be technologically generated.
“We need to distinguish the exciting radio signals in space from the uninteresting radio signals from Earth,” said study lead author Peter Ma, an undergraduate student majoring in Physics at the University of Toronto.
By using this groundbreaking algorithm, the scientists examined over 150 TB of data from 820 nearby stars, on a dataset which had previously been searched through in 2017 by classical techniques, but considered as devoid of any interesting signals. However, the eight signals recently detected through this technique resemble quite closely what astronomers expect extraterrestrial signals to look like.
By contrast to signals caused by natural phenomena, which tend to be broadband, these signals were narrow band. Moreover, they exhibited what is known as a “slope,” meaning that their origin had a certain degree of relative acceleration with our antennas, and thus suggesting that they were not coming from Earth. Finally, while human radio interference usually occurs in both ON and OFF observations since their source is close by, these signals appeared only in ON-source observations.
“First, they are present when we look at the star and absent when we look away, as opposed to local interference, which is generally always present. Second, the signals change in frequency over time in a way that makes them appear far from the telescope,” explained study co-author Steve Croft, a project scientist at Breakthrough Listen, the world’s largest research program aimed at finding evidence of extraterrestrial civilizations.
Unfortunately, the scientists were unable to detect the radio signals again through follow-up observations. Nevertheless, these findings highlight the power of using machine learning techniques in exploring our universe and possibly put us in contact with other civilizations.
“We’re scaling this search effort to one million stars today with the MeerKAT telescope and beyond. We believe that work like this will help accelerate the rate we’re able to make discoveries in our grand effort to answer the question ‘are we alone in the universe?’” Ma concluded.
The study is published in the journal Nature Astronomy.
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