Asteroseismic fundamental properties of solar-type stars observed by the NASA Kepler mission

We use asteroseismic data obtained by the NASA Kepler mission to estimate the fundamental properties of more than 500 main-sequence and sub-giant stars. Data obtained during the first 10 months of Kepler science operations were used for this work, when these solar-type targets were observed for one month each in survey mode. Stellar properties have been estimated using two global asteroseismic parameters and complementary photometric and spectroscopic data. Homogeneous sets of effective temperatures, T eff, were available for the entire ensemble from complementary photometry; spectroscopic estimates of T eff and [Fe/H] were available from a homogeneous analysis of ground-based data on a subset of 87 stars. We adopt a grid-based analysis, coupling six pipeline codes to 11 stellar evolutionary grids. Through use of these different grid-pipeline combinations we allow implicitly for the impact on the results of stellar model dependencies from commonly used grids, and differences in adopted pipeline methodologies. By using just two global parameters as the seismic inputs we are able to perform a homogenous analysis of all solar-type stars in the asteroseismic cohort, including many targets for which it would not be possible to provide robust estimates of individual oscillation frequencies (due to a combination of low signal-to-noise ratio and short dataset lengths). The median final quoted uncertainties from consolidation of the grid-based analyses are for the full ensemble (spectroscopic subset) approximately 10.8% (5.4%) in mass, 4.4% (2.2%) in radius, 0.017 dex (0.010 dex) in log g, and 4.3% (2.8%) in mean density. Around 36% (57%) of the stars have final age uncertainties smaller than 1 Gyr. These ages will be useful for ensemble studies, but should be treated carefully on a star-by-star basis. Future analyses using individual oscillation frequencies will offer significant improvements on up to 150 stars, in particular for estimates of the ages, where having the individual frequency data is most important.