From the Mountaintops of West Virginia to pastures in Australia’s countryside, astronomers use some of the globe’s most massive telescopes dreaming of finding signals sent by possible extraterrestrial societies.
SETI (Search for Extraterrestrial Intelligence) is an exploratory effort to detect artificial electromagnetic radiation produced by a distant advanced civilization in the universe. The distinct signal could prove that alien life exists elsewhere in the cosmos.
A new paper1 released today proposes how machine learning (ML) and artificial intelligence (AI) can be used to quickly make sense of the vast amount of data gathered in the pursuit of discovering extraterrestrial life. Looking ahead, AI-powered technology offers great potential in searching for any signs that could prove our presence beyond.
Franck Marchis says:
“It is a new era for SETI research that is opening up thanks to machine learning technology,
For decades, SETI was hindered due to limited data; however, the issue of big data is fairly new. In 1960, Frank Drake initiated SETI by poInting a telescope in Green Bank, West Virginia, at two stars and searching for radio transmissions.
Subsequent SETI searches were also, unfortunately, restricted to examining only a few stars. Many were limited in scope and did not consider a wider range of targets.
In 2015, Yuri Milner, a billionaire, supported and funded The Breakthrough Listen Project in Berkeley, California, the biggest SETI project ever. This mission was created to scan over one million stars for signs of intelligent extraterrestrial life.
The project, utilizing telescopes in West Virginia, Australia, and South Africa, searches for radio waves from nearby stars. In particular, they focus on varying frequencies to reveal patterns betokening a possible alien transmitter on a planet as it orbits the Earth.
Data Blizzard
The modern world produces interference which affects searches, resulting in many false positives being shown. Unfortunately, these extraneous signals generated by sources such as mobile phones or GPS complicate the task, producing a deluge of data to sift through to find a correct result.
Sofia Sheikh says:
“The biggest challenge for us in looking for SETI signals is not at this point getting the data,”
“The difficult part is differentiating signals from human or Earth technology from the kind of signals we’d be looking for from technology somewhere else out in the Galaxy.”
Considering the impracticality of manually analyzing millions of observations, many exploration programs leverage algorithmic processes to detect signs providing akin characteristics to supposed extraterrestrial 911 signals.
Those algorithms can miss possible signals that may be of interest but differ slightly from the conventional expectations of astronomers.
Overlooked Signals
Dan Werthimer, the SETI scientist at the University of California, Berkeley, believes that apart from successfully categorizing various signals, machine learning is adept at spotting even those candidate extraterrestrial signals that differ from the traditional ones – something that earlier methods would not have conventionally detected.
Peter Ma, a mathematician and physicist at the University of Toronto, Canada, and the lead author of today’s paper, agrees.
Peter Says:
“We can’t always be anticipating what ET might send to us”
Ma and his team analyzed the Breakthrough Listen scans of 820 stars from the observations tracked using the Robert C. Byrd Green Bank Telescope 100m in diameter.
Their developed AI-infused software pored through the inputted data, taking note of nearly three million cues but discarding most due to terrestrial interference. From here, Ma looked at about 20,000 signals more closely and identified 8 that warranted additional investigation.
Even if aliens are out there trying to communicate with us, they might not be using any form of electromagnetic radiation that we can currently detect. If this is the case, we may never know that they exist unless they come here themselves- which raises a whole other set of questions. In the meantime, we will keep searching for signals from space, hoping that one day we might find something- even if it’s just an AI.
Source: www.nature.com
