How NASA Uses Artificial Intelligence to Detect Exoplanets
According to NASA scientists, there are around 100 billion stars in the universe, with 40 billion having a planet orbiting them that can potentially host life. This blog post shares insights into how NASA employs machine learning and transit techniques to detect exoplanets and trace down such biohints as water to confirm the existence of human-like forms of life. For instance, the article overviews how transmission spectroscopy is applied to measure atmospheric spectrum, which is essential to understanding what a planet’s size and atmospheric properties are. In addition, the story sheds some light onto the agency’s PSG tool, which provides a three-dimensional orbital calculator for most bodies in the Solar system and all the confirmed exoplanets. Finally, you will also learn about the INARA tool used to generate spectra of rocky planets and to train a machine learning model for retrieving atmospheric parameters.
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