It's been thirty years since the first scientific proof of the existence of planets outside the solar system was received. At the time of this publication, the official status of exoplanets was 3767 objects with a total number of candidates more than 4,500.
Most of these planets are very severe and completely unsuitable for life worlds, but some of them, according to scientists, still may have suitable conditions for its occurrence. At least they are not too hot and at the same time not too cold in order to maintain the presence of water on their surface in a liquid form. And water, as you know, is one of the sources of life.
Of course, the main reason for finding new exoplanets is to find life outside the Earth. Why else spend a lot of money building new telescopes and creating new technologies for exploring outer space? Therefore, scientists from Columbia University (USA) have developed a new system that can simplify the "hunt" for potentially inhabited worlds. Using algorithms of machine learning, the researchers created a technology that allows to more effectively determine the possibility of survival of an exoplanet in a stable orbit.
In this work, the researchers focused on the so-called "Tattoins", or exoplanets, revolving around double stars, just like Luke Skywalker's own desolate world from "Star Wars". Formally known in scientific circles as circumambinary planets, they can undergo enormous orbital changes, since they are always in a gravitational pool of two stars at once. Attracting one to one star, then to another, they risk eventually be thrown out of the system, and in the worst case - to fall on one of their luminaries.
Scientists have derived an equation that helps determine the long-term stability of the orbit of the circumnar planets, however, according to Chris Lam, the head of development, which is currently being discussed, this equation can not give accurate data taking into account all possible circumstances.
"The problem is that if there are three or more bodies in the system, the motion becomes" chaotic, "as physicists and mathematicians say," Lam comments.
"Therefore, there are borderline cases where the equation predicts that the system is unstable when it is actually stable, and vice versa. We decided that the neural network will help us to cope with this problem. "
The ability to predict whether a planet will be thrown out of its system is not just a whim, it is an additional opportunity to determine the habitation potential of a particular world. In the end, for the emergence and development of life, at least the one that exists on Earth, it took several billion years. In other words, for it there will be no chance, if it is a question of a planet wandering in space and not attached to its luminary.
For a more effective method of determining the survival of the "Tatooine," Lam and his colleagues created an algorithm for machine learning, which scientists trained with the help of 10 million simulated similar planets. As Lam notes, after several hours of experimentation and tuning, the system was able to surpass the accuracy of the traditional equation "in all respects."
Scientists expect that the new space telescope TESS of the NASA aerospace agency, recently successfully put into orbit, will be able to discover many new circumnar planets, and the development of researchers from Columbia University, Lam believes, can help in the study of these worlds.
"Our model will help astronomers understand which regions are best suited for searching for planets around binary systems. This, I hope, will help us not only to discover new exoplanets, but also to better understand their features, "the scientist noted.
The article is based on materials .
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