Signals from space: Using a new AI system, astronomers have identified eight possible technosignatures from extraterrestrial intelligence using radio signals.
The radio signals come from five stars between 30 and 90 light-years away from us. The characteristics of the signals do not match either terrestrial or known astronomical radio sources. However, it has not yet been possible to capture further signals from these sources.
Astronomers have been listening out into space for decades to capture possible technosignatures — radio signals from an extraterrestrial civilization. So far, however, in vain. In 1977, the SETI project detected a strong radiation pulse that could not be explained by terrestrial or astronomical radio sources. However, this “wow signal” never appeared again and its origin is largely unknown. Other candidates, such as the BLC1 signal putatively from Proxima Centauri in 2020, later turned out to be of terrestrial origin.
The problem: Radio telescopes pick up a plethora of signals that form a dense noise floor. “The vast majority of the signals detected by our telescopes come from our own technology — GPS satellites, cell phones and the like,” explains co-author Steve Croft of the University of California at Berkeley. “The search for technosignatures from an alien civilization is therefore akin to looking for a needle in a haystack.”
In order to find potential signals of extraterrestrial origin in this jumble of radio waves, astronomers in projects such as SETI and Breakthrough Listen use special algorithms. From the data recorded by the telescopes, these first filter out the radio signals from known terrestrial sources of interference and from known astronomical radio sources such as pulsars. Still, this is often not enough to separate potential techno signatures from background noise.
A new AI system has now put things right. This technology, developed by first author Peter Ma from the University of Toronto, can search radio data more thoroughly than before and even pick out weaker techno signatures from heavy noise floors. This is made possible by two adaptive algorithms connected in series. The first AI system, a so-called autoencoder, is trained on the typical characteristics of technosignatures using signals intentionally inserted into raw data.
Typical features include a very narrow bandwidth, a highly localized origin, and a rate of drift—a modulation in the signal that indicates a source that is moving relative to us. After the first AI system has learned this, it transfers this knowledge to a second algorithm, the so-called Random Forest Classifier. The latter then takes over the actual filtering and identifies potential alien signals in the raw data it has examined.
For their current study, Ma and his team applied this method to data from a sky survey by the Green Banks radio telescope in the United States. “We searched a total of 150 terabytes of data from 820 nearby stars,” reports Ma. This radio data had previously been analyzed by classical algorithms, which had found nothing.
But this time it was different: The AI system developed by Ma discovered eight radio signals that have typical characteristics of techno signatures. “These eight signals, classified as interesting, come from five different stars that are between 30 and 90 light-years away from us,” the astronomers report. One star, HIP 62207, is a Sun-like star, three stars are slightly cooler and redder than the Sun, and one is a whitish giant star.
All eight signals have a narrow frequency range and exhibit drift typical of an extraterrestrial origin, the team reports. The radio pulses, each lasting only a few minutes, could only be detected when the telescope pointed to their stellar origin.
However: All eight signals occurred only once and can therefore not be analyzed or traced in more detail. Even during a targeted follow-up observation of the five stars with the Green Bank radio telescope in May 2022, the astronomers could no longer find any comparable radio signals. “Therefore, we cannot say definitively whether these eight signals really come from extraterrestrial intelligences,” Ma and his colleagues emphasize.
However, the astronomers advocate keeping an eye on the five stars and regularly listening for potential technosignatures. They want to use their new AI system for signal searches in the data from other radio telescopes in the future. The next plan is to use it on the MeerKAT array in South Africa. “We’re expanding our search to around a million stars,” says Ma. “This will help us find answers to the question of whether we are alone in the universe.” (Nature Astronomy, 2023; doi: 10.1038/s41550-022-01872-z)
Quelle: SETI-Institute, University of Toronto, Breakthrough Initiatives
This article was written by Nadja Podbregar
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The original of this article “Astronomers discover eight potential alien signals” comes from scinexx.
