KEPLER AUTOREGRESSIVE PLANET SEARCH

NASA'S KEPLER MISSION IS THE SOURCE OF MORE EXOPLANETS THAN ANY OTHER INSTRUMENT BUT THE DISCOVERY DEPENDS ON COMPLEX STATISTICAL ANALYSIS PROCEDURES EMBEDDED IN THE KEPLER PIPELINE. A PARTICULAR CHALLENGE IS MITIGATING IRREGULAR STELLAR VARIABILITY WITHOUT LOSS OF SENSITIVITY TO FAINT PERIODIC PLANETARY TRANSITS. THIS PROPOSAL PRESENTS A TWO-STAGE ALTERNATIVE ANALYSIS PROCEDURE. FIRST PARAMETRIC AUTOREGRESSIVE ARFIMA MODELS COMMONLY USED IN ECONOMETRICS REMOVE MOST OF THE STELLAR VARIATIONS. SECOND A NOVEL MATCHED FILTER IS USED TO CREATE A PERIODOGRAM FROM WHICH TRANSIT-LIKE PERIODICITIES ARE IDENTIFIED. THIS ANALYSIS PROCEDURE THE KEPLER AUTOREGRESSIVE PLANET SEARCH (KARPS) IS ING MOST OF THE KEPLER OBJECTS OF INTEREST AND IS EXPECTED TO IDENTIFY ADDITIONAL PLANETARY CANDIDATES. THE PROPOSED RESEARCH WILL COMPLETE APPLICATION OF THE KARPS METHODOLOGY TO THE PRIME KEPLER MISSION LIGHT CURVES OF 200 000: STARS AND COMPARE THE RESULTS WITH KEPLER OBJECTS OF INTEREST OBTAINED WITH THE KEPLER PIPELINE. WE WILL THEN CONDUCT A VARIETY OF ASTRONOMICAL STUDIES BASED ON THE KARPS RESULTS. IMPORTANT SUBSAMPLES WILL BE EXTRACTED INCLUDING HABITABLE ZONE PLANETS HOT SUPER-EARTHS GRAZING-TRANSIT HOT JUPITERS AND MULTI-PLANET SYSTEMS. GROUND-BASED SPECTROSCOPY OF POORLY STUDIED CANDIDATES WILL BE PERFORMED TO BETTER CHARACTERIZE THE HOST STARS. STUDIES OF STELLAR VARIABILITY WILL THEN BE PURSUED BASED ON KARPS ANALYSIS. THE AUTOCORRELATION FUNCTION AND NONSTATIONARITY MEASURES WILL BE USED TO IDENTIFY SPOTTED STARS AT DIFFERENT STAGES OF AUTOREGRESSIVE MODELING. PERIODIC VARIABLES WITH FOLDED LIGHT CURVES INCONSISTENT WITH PLANETARY TRANSITS WILL BE IDENTIFIED THEY MAY BE ECLIPSING OR MUTUALLY-ILLUMINATING BINARY STAR SYSTEMS. CLASSIFICATION OF STELLAR VARIABLES WITH KARPS-DERIVED STATISTICAL PROPERTIES WILL BE ATTEMPTED. KARPS PROCEDURES WILL THEN BE APPLIED TO ARCHIVED K2 DATA TO IDENTIFY PLANETARY TRANSITS AND CHARACTERIZE STELLAR VARIABILITY.