Abstract
The rapidly increasing volume of asteroseismic observations on solar-type stars has revealed a need for automated analysis tools. The reason for this is not only that individual analyses of single stars are rather time consuming, but more importantly that these large volumes of observations open the possibility to do population studies on large samples of stars and such population studies demand a consistent analysis. By consistent analysis we understand an analysis that can be performed without the need to make any subjective choices on e.g. mode identification and an analysis where the uncertainties are calculated in a consistent way. Here we present a set of automated asterosesimic analysis tools. The main engine of these set of tools is an algorithm for modelling the autocovariance spectra of the stellar acoustic spectra allowing us to measure not only the frequency of maximum power and the large frequency separation, but also the small frequency separation and potentially the mean rotational rate and the inclination. The measured large and small frequency separations and the frequency of maximum power are used as input to an algorithm that estimates fundamental stellar parameters such as mass, radius, luminosity, effective temperature, surface gravity and age based on grid modeling. All the tools take into account the window function of the observations which means that they work equally well for space-based photometry observations from e.g. the NASA Kepler satellite and ground-based velocity observations from e.g. the ESO HARPS spectrograph.
| Original language | English |
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| Journal | Astronomische Nachrichten |
| ISSN | 0004-6337 |
| Publication status | Published - 2010 |