Searching for exoplanets using artificial intelligence

• Published in: Monthly notices of the Royal Astronomical Society Vol. 474; no. 1; pp. 478 - 491
• Main Authors: Pearson, Kyle A., Palafox, Leon, Griffith, Caitlin A.
• Format: Journal Article
• Language: English
• Published: London Oxford University Press 01.02.2018
• Subjects: Artificial intelligence; Artificial neural networks; Astronomy; Extrasolar planets; Feature recognition; Human error; Interpolation; Least squares method; Machine learning; Neural networks; Planet detection; Time series; Transits; planets and satellites: detection; techniques: photometric; methods: data analysis

Abstract In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labour intensive and subject to human error, the results of which are difficult to quantify. Here we present a new method of detecting exoplanet c...