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Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys

Machine-learning approaches to exoplanet transit detection and candidate validation in wide-field ground-based surveys

Since the start of the Wide-angle Search for Planets (WASP) program, more than 160 transiting exoplanets have been discovered in the WASP data. In the past, possible transit-like events identified by the WASP pipeline have been vetted by human inspection to eliminate false alarms and obvious false positives. The goal …