False positive probabilties for all Kepler Objects of Interest: 1284 newly validated planets and 428 likely false positives

TL;DR

This paper introduces a fully automated method to calculate false positive probabilities for all Kepler Objects of Interest, validating 1284 new planets and identifying 428 likely false positives, using the 'vespa' tool.

Contribution

It provides the first large-scale, automated validation of Kepler planet candidates and offers stellar property posteriors for all hosts.

Findings

Validated 1284 new planets with <1% false positive probability.

Identified 428 likely false positives among Kepler candidates.

Developed and applied the 'vespa' Python package for automated validation.

Abstract

We present astrophysical false positive probability calculations for every Kepler Object of Interest (KOI)---the first large-scale demonstration of a fully automated transiting planet validation procedure. Out of 7056 KOIs, we determine that 1935 have probabilities <1% to be astrophysical false positives, and thus may be considered validated planets. 1284 of these have not yet been validated or confirmed by other methods. In addition, we identify 428 KOIs likely to be false positives that have not yet been identified as such, though some of these may be a result of unidentified transit timing variations. A side product of these calculations is full stellar property posterior samplings for every host star, modeled as single, binary, and triple systems. These calculations use 'vespa', a publicly available Python package able to be easily applied to any transiting exoplanet candidate.