Oscillation frequencies for 35 Kepler solartype planethosting stars using Bayesian techniques and machine learning
Abstract
Kepler has revolutionized our understanding of both exoplanets and their host stars. Asteroseismology is a valuable tool in the characterization of stars and Kepler is an excellent observing facility to perform asteroseismology. Here we select a sample of 35 Kepler solartype stars which host transiting exoplanets (or planet candidates) with detected solarlike oscillations. Using available Kepler short cadence data up to Quarter 16 we create power spectra optimized for asteroseismology of solartype stars. We identify modes of oscillation and estimate mode frequencies by `peak bagging' using a Bayesian Markov Chain Monte Carlo framework. In addition, we expand the methodology of quality assurance using a Bayesian unsupervised machine learning approach. We report the measured frequencies of the modes of oscillation for all 35 stars and frequency ratios commonly used in detailed asteroseismic modelling. Due to the high correlations associated with frequency ratios we report the covariance matrix of all frequencies measured and frequency ratios calculated. These frequencies, frequency ratios, and covariance matrices can be used to obtain tight constraint on the fundamental parameters of these planethosting stars.
 Publication:

Monthly Notices of the Royal Astronomical Society
 Pub Date:
 February 2016
 DOI:
 10.1093/mnras/stv2593
 arXiv:
 arXiv:1511.02105
 Bibcode:
 2016MNRAS.456.2183D
 Keywords:

 asteroseismology;
 planets and satellites: fundamental parameters;
 stars: evolution;
 stars: fundamental parameters;
 stars: oscillations;
 planetary systems;
 Astrophysics  Solar and Stellar Astrophysics
 EPrint:
 83 pages, 103 figures, accepted for publication in MNRAS