Statistics – Methodology
Scientific paper
Jan 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aas...21345503l&link_type=abstract
American Astronomical Society, AAS Meeting #213, #455.03; Bulletin of the American Astronomical Society, Vol. 41, p.354
Statistics
Methodology
Scientific paper
Of the approximately 300 known extrasolar planetary systems, 30 are known to harbor multiple planets. Further, analysis of residuals for systems with long-term radial velocity (RV) observations suggests that over 30% of systems with one known planet harbor at least one additional giant planet with a longer orbital period; this frequency may rise rapidly as sensitivity to lower mass planets improves. About a third of the known multiple systems appear to have planets in low-order mean-motion resonances (MMRs); the dynamics of these systems can help constrain models of planet migration. Most current exoplanet data analysis methodology relies on Keplerian orbit models for planet detection and measurement. But the motions of interacting planets are not precisely Keplerian, raising questions about the suitability and sensitivity of current methods for studying interacting systems. We are investigating the ability of Keplerian orbit models to detect and accurately measure interacting planets in astrometry data expected from SIM, supplemented by long-term RV data. We are generating ensembles of systems with a variety of planet masses, periods, and eccentricities, including planets with 2:1 and 3:1 MMRs (future work will explore higher order and double resonances). We use Burlish-Stoer n-body integration to calculate the orbits, and then simulate astrometric data as expected from SIM, and supplementary RV data. We use a data analysis pipeline that relies on several generalized periodograms for period searching, followed by detailed Keplerian orbit fitting using Bayesian methods. This presentation describes the data analysis pipeline, and presents initial results for example interacting systems.
Ford Eric B.
Loredo Thomas
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