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New signals identified in the search for extraterrestrial life

If they’re out there, then why haven’t we found them yet? New research led by undergraduate student Peter Ma at the University of Toronto, along with scientific research institutions around the world, has uncovered eight previously unidentified signals of interest.

The study used a dataset that had previously been searched through in 2017 that was labeled as devoid of interesting signals. 

“We’re scaling this search effort to 1 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?’” said Ma.

The search for extraterrestrial intelligence (SETI) beyond Earth aims to detect evidence of alien technology by searching for radio signals. Radio can send information over incredible distances at the speed of light (about 20,000 times faster than our best rockets). Many SETI efforts use antennas to eavesdrop on any radio signals aliens might be transmitting.

The experts re-examined data taken as part of a Breakthrough Listen campaign that initially indicated no targets of interest. The team applied new, deep learning techniques to yield faster and more accurate results. 

After running the new algorithm and re-examining the data to confirm the results, newly detected signals were found. These included several key characteristics:

  1. The signals had a narrow spectral width of just a few hertz. Signals caused by natural phenomena tend to be broadband.
  2. The signals had non-zero drift rates, which means the signals had a slope. This could indicate a signal’s origin had some relative acceleration with our receivers, not local to the radio observatory.
  3. The signals appeared in ON-source observations and not in OFF-source observations. If a signal originates from a specific celestial source, it appears when we point our telescope toward the target and disappears when we look away. Human radio interference usually occurs in ON and OFF observations due to the source being close by.

Cherry Ng, astronomer at both the SETI Institute and the French National Center for Scientific Research said, 

“These results dramatically illustrate the power of applying modern machine learning and computer vision methods to data challenges in astronomy, resulting in both new detections and higher performance. Application of these techniques at scale will be transformational for radio techno signature science.”

This new approach can help researchers more effectively understand the data they collect and act quickly to re-examine targets. Ma and his advisor Dr. Cherry Ng are looking forward to deploying extensions of this algorithm on the SETI Institute’s COSMIC system.

Since SETI experiments began in 1960, technological advances have enabled researchers to collect more data than ever. This requires new tools to process and analyze that data quickly to identify evidence of extraterrestrial intelligence, breaking new ground in the quest to answer the question: “Are we alone?”

The research is published in the journal Nature Astronomy.

By Katherine Bucko, Staff Writer

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