Kepler Planet Detection Metrics: Automatic Detection of Background Objects Using the Centroid RobovetterWe present an automated method of identifying background eclipsing binaries masquerading as planet candidates in the Kepler planet candidate catalogs. We codify the manual vetting process for Kepler Objects of Interest (KOIs) described in Bryson et al. (2013) with a series of measurements and tests that can be performed algorithmically. We compare our automated results with a sample of manually vetted KOIs from the catalog of Burke et al. (2014) and find excellent agreement. We test the performance on a set of simulated transits and find our algorithm correctly identifies simulated false positives approximately 50 of the time, and correctly identifies 99 of simulated planet candidates.
Document ID
20170009552
Acquisition Source
Ames Research Center
Document Type
Other
Authors
Mullally, Fergal (Search for Extraterrestrial Intelligence Inst. Moffett Field, CA, United States)