Scientists point out the limitations of our current searches as an answer to handwringing about our inability to discover proof of life outside of the Solar System. However, even if our equipment have detected a signal, we might have missed it if we combed the data with decades-old techniques.
The use of data from a significant radio telescope in a machine learning-based selection process has made the theory more tenable. In comparison to earlier observations, the system found 100 times more patterns in the noise that warranted further analysis.
Eight of these are sufficiently intriguing to warrant follow-up investigations, according to a research in Nature Astronomy, even if none of them have yet produced convincing evidence of extraterrestrial life—you would have heard about it if they had. This is all based on a very small portion of humankind’s radio telescope recordings.
The Robert C. Byrd Green Bank radio telescope was used to observe 820 stars for 480 hours as part of SETI Breakthrough’s hunt for radio signals that might point to the existence of extraterrestrial civilizations.
Nobody is prepared for a deliberate transmission like the one from Contact that is sent directly to Earth. Astronomers prefer to expect stray leaking. However, it is difficult to recognise this since it must be distinguished from both Earth-based and satellite sources as well as from natural radio waves. How difficult it can be to distinguish between these is demonstrated by the apparent signal known as BCL1, which was previously supposed to originate from Proxima Centauri.
Breakthrough The first 2.9 million “signals of interest” found by Listen’s technology were reduced to 20,515 that merited human attention. Comparatively, 200 were discovered in the same data using earlier techniques.
In an effort to replicate their success, the writers followed up eight (MLc1-8) from seven stars. The system’s sensitivity gives the team hope despite the fact that the re-examination failed.
The MeerKAT telescope is being used to scale up this search to 1 million stars and beyond. In a statement sent by email, main author Peter Ma, a student at the University of Toronto, stated, “We think that work like this will assist expedite the pace we’re able to make discoveries in our big endeavour to answer the question ‘are we alone in the universe?’.”
Ma looked at data that had been gathered years before, which diminished the likelihood that she would discover anything. The ability to examine data more quickly will enable the team to do follow-up investigations more swiftly, which excites them.
Dr. Franck Marchis of SETI, who was not an author on the work, expressed regret that, despite efforts described by the team, these signals could not be verified by additional instruments in a message issued to IFLScience. The MLc1 and MLc7 signals are highly intriguing because they were detected on two separate occasions, indicating that, if they are terrestrial in origin, they are not known interference. Before we can be certain that we have discovered extraterrestrial life, such a discovery needs to be verified by other equipment. However, this scientific finding demonstrates that it is currently feasible to disclose this type of identification promptly enough to conduct the required follow-up.
The introduction of massive networks like MeerKAT and the SKA, which will generate terabytes of data each week, makes it essential for SETI research to adopt potent techniques like deep learning, according to Marchis. “We anticipate that this approach will be able to pick up a signal more quickly than current techniques, enabling us to validate the signal’s extraterrestrial origin by using additional antennas.
