Researchers used machine learning tools to confirm evidence of a planet outside our solar system. According to their findings, machine learning can accurately predict whether a newly formed star will host an exoplanet.
Using machine learning to identify previously overlooked exoplanets. It is the first step towards using machine learning to find exoplanets, according to the researchers.
According to Jason Terry, lead author of the study, we confirmed the planet using traditional techniques. But our models guided us to run simulations and revealed its exact location. The University of Georgia is home to Terry, a doctoral student.
Using machine learning models, researchers were able to suggest the existence of a planet using older astronomical observations. The images demonstrated this by highlighting a particular segment of the protoplanetary disc, or rotating disk of dense gas surrounding a newly born star.
The researchers noticed that the velocity of the gas in that region of the disc fluctuated oddly, which indicates a planet. Until now, Cassandra Hall says machine learning will use it only for discovering known exoplanets in formation. Discoveries can now be made using models as the researchers have proven.
A model was able to detect a signal that other researchers had already analyzed, whereas others had not been able to do so. Consequently, machine learning can identify important information quickly and accurately that people are likely to miss, according to Terry.
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