A Machine Learning Algorithm Finds its First Supernova

Plenty of recent mainstream news articles have touted AI’s ability to assist in the process of scientific discovery. But most of them predicted that it could take years or even decades to see the full effect. Astronomy seems ahead of the curve, though, with the announcement of a new AI system developed by researchers at Northwestern University and elsewhere that can now autonomously detect and classify supernovae.

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Machine Learning Algorithm Scoops up 50 New Exoplanets

Credit: NASA/JPL-Caltech

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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