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Astronomers have discovered eight "suspicious" radio signals that they say could be evidence of "technological life beyond Earth."
A team of experts led by University of Toronto student Peter Ma developed a new artificial intelligence algorithm that helped them discover these stars after observing 820 stars using the Green Bank Telescope in West Virginia. Signal.
According to IT House, the artificial intelligence algorithm uses machine learning to distinguish signals caused by humans - such as signals from GPS satellites and mobile phones, and alien signals. Due to interference, these eight suspicious signals were not detected in past observations by the Green Bank Telescope.
"We need to distinguish exciting radio signals in space from those coming from Earth," Ma declared in his paper, published late last month in the journal Nature Astronomy . He said that while these eight signals were not conclusive evidence of life beyond Earth, they were certainly unexplainable.
Researchers created this graphic showing these eight strange signals
Our The vast majority of signals detected by telescopes come from the earth. The reason why these eight signals may come from extraterrestrial planets is because they are "narrowband", while signals caused by humans are often "broadband". Additionally, these signals have a "slope," meaning the signal's source has some acceleration relative to our antenna, so it cannot come from Earth.
These results greatly illustrate the power of applying modern machine learning and computer vision methods to data analysis in astronomy, and their large-scale application will be transformative to the science of radio technology signatures.
Peter Ma hopes to use artificial intelligence algorithms to examine more stars and a wider range of space, eventually hoping to expand the effort to examine 1 million stars through the MeerKAT telescope in South Africa. He believes this work will help speed up our efforts to answer the question: Are we alone in the universe?
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