Machine Learning Algorithm Scoops up 50 New Exoplanets

Advances in technology are having a profound impact on astronomy and astrophysics. At one end, we have advanced hardware like adaptive optics, coronographs, and spectrometers that allow for more light to be gathered from the cosmos. At the other end, we have improved software and machine learning algorithms that are allowing for the data to be analyzed and mined for valuable nuggets of information.

One area of research where this is proving to be invaluable is in the hunt for exoplanets and the search for life. At the University of Warwick, technicians recently developed an algorithm that was able to confirm the existence of 50 new exoplanets. When used to sort through archival data, this algorithm was able to sort through a sample of candidates and determine which were actual planets and which were false positives.

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