A new artificial intelligence algorithm created by a Toronto student is helping researchers look for signs of life among the stars.
Peter Xiangyuan Ma, a student and researcher at the University of Toronto, said he started working on the algorithm while in Grade 12 during the pandemic.
“I was just looking for projects and I was interested in astronomy,” he told CTV News Toronto.
The idea was to help distinguish between technological radio signals created by human technology and signals potentially coming from other life forms in space.
“What we’re looking for are signs of technology that indicate whether the sender is intelligent or not.” And so unsurprisingly for us, we continue to find each other,” explained Ma. “We don’t want to look at our own noisy signals.”
Using this algorithm, Ma said the researchers were able to detect eight new radio signals emitted by five different stars about 30 to 90 light-years from Earth.
Those signals, Ma said, will disappear when researchers look away from it, which largely rules out interference from a signal coming from Earth. When they returned to the area, the signal was still there.
“We’re all very suspicious and scratching our heads,” he said. “We’ve proven that we’ve found things we wanted to find… now, what do we do with it all? That is another separate matter.”
Steve Croft, project scientist for Breakthrough Listen on the Green Bank Telescope, the institute whose open-source data inspired Ma’s algorithm, said finding radio signals in space is like trying to find a needle in a haystack.
“You have to recognize the haystack itself and make sure you don’t drop the needle while looking at the individual pieces of hay,” Croft, who collaborated on Ma’s research, told CTV News Toronto.
An image of the Green Bank Telescope is seen here. (Credit Break Listen / Steve Croft)
Croft said the algorithms used to detect these signals must take into account multiple characteristics, including the position they come from in the sky and whether the transmission changes over time, which can indicate whether it’s coming from a rotating planet or star.
“The algorithm that Peter developed allowed us to do this more efficiently,” he said.
The challenge, Croft says, is recognizing that false positives can exist even though the signal meets that criterion. What could be signs of extraterrestrial life could also just be “a strangely shaped haystack,” he added.
“And so we have to go back and look again and see if the signal is still there. And with these particular examples that Peter found with his algorithm, the signal was gone when we pointed the telescope back again. And so we kind of can’t say one way or the other, is this real?”
Researchers have been searching the skies for technologically generated signals since the 1960s, scouring thousands of stars and galaxies for signs of intelligent life. The process is called “SETI” or “Search for Extraterrestrial Intelligence”.
But interference from our own radio signals has always proved a challenge. Croft says most pieces of technology have some kind of Bluetooth or wireless wave element that creates static electricity, leading to larger amounts of data needed to be collected.
“It’s a challenge, but computers also provide the solution,” he said.
“So computing and especially machine learning algorithms give us the power to search through that big haystack, looking for the needle of an interesting signal.”
Ma said that although we haven’t found a “technosignal” yet, we shouldn’t give up. The next step would be to use multiple types of search algorithms to find more and more signals to research.
Peter Ma is seen in this photo taken in 2021. (Adar Kahiri)
While the “dream” is to find evidence of life, Ma says he is more focused on the scientific effort to actively search for it.
This sentiment is echoed by Croft, who said he is most fascinating in his work to answer the question of whether humans are alone in this universe.
“I don’t show up to work every day thinking I’m going to find aliens, but I do. So, you know, I have some optimism.
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