Humanity has been trying to contact extraterrestrial civilizations for nearly 50 years. Even longer than she listens to space in the hope of picking up a message from elsewhere. But it is very difficult to hear something of which we are unaware even of its form. Today, researchers are working on algorithms that could advance our knowledge in this area.
An international team led by the University of California at Berkeley and the Seti Institute (United States) has developed a new machine learning tool intended to simulate what a message from a and which presents itself as a library open-source likely to be a game-changer for future searches for extraterrestrial intelligences.extraterrestrial. A tool called
Let us recall that in theEarth scientists first looked for signals whose origin is clearly artificial. It was the objective of directed in 1960 by the famous Cornell Frank Drake. Research then focused on the at which hydrogen emits radiation into interstellar space: 1.42 gigahertz (GHz). A very widespread natural material, supposedly known by any potential intelligent extraterrestrial civilization which would use it to maximize the chances of its message being heard. But nothing.
It’s hard to imagine a technological activity different from ours
So the search extended. To other frequency ranges — over a multi-gigahertz band — to different regions of the sky, and even to other types of signals. And still nothing. All of this comes up against a major obstacle: the fact that humanity has never yet recorded an extraterrestrial signal. A signal on which we could base our experiment. And that would better guide researchers.
Algorithms based onhave begun to be used to distinguish possible extraterrestrial transmissions from background noise. The best known serves the program BreakthroughListen. It aims to identify continuous signals such as those that are easy and inexpensive in to produce on Earth. So always looking for signs of technological activity as we know it.
It is to overcome this difficulty that researchers have now developed a library intended to be regularly updated according in particular to the advances made possible by the integration in the search for intelligent extraterrestrial civilizations of increasingly more perfected. This library should facilitate the production of synthetic extraterrestrial signals. These can then be used as such or added to observation data. Enough to produce large data sets of synthetic signals to analyze the sensitivity of existing algorithms or to serve as a basis for machine learning. And develop new research methods. The ultimate goal is to successfully establish parameters that can overcome the assumptions made by researchers about what an extraterrestrial message might look like.
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If aliens sent us a message, what would it look like?
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