Challenges for asteroseismic analysis of Sun-like stars
School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK e-mail: firstname.lastname@example.org
2 Institute of Astronomy, University of Cambridge, Cambridge CB3 0HA, UK e-mail: email@example.com
3 Institut d'Astrophysique Spatiale (IAS), Batiment 121, 91405 Orsay Cedex, France
4 Faculty of Arts, Computing, Engineering and Sciences, Sheffield Hallam University, Sheffield S1 1WB, UK
Accepted: 22 April 2008
Context. Asteroseismology of Sun-like stars is undergoing rapid expansion with, for example, new data from the CoRoT mission and continuation of ground-based campaigns. There is also the exciting upcoming prospect of NASA's Kepler mission, which will allow the asteroseismic study of several hundred Sun-like targets, in some cases for periods lasting up to a few years.
Aims. The seismic mode parameters are the input data needed for making inference on stars and their internal structures. In this paper we discuss the ease with which it will be possible to extract estimates of individual mode parameters, dependent on the mass, age, and visual brightness of the star. Our results are generally applicable; however, we look at mode detectability in the context of the upcoming Kepler observations.
Methods. To inform our discussions we make predictions of various seismic parameters. To do this we use simple empirical scaling relations and detailed pulsation computations of the stochastic excitation and damping characteristics of the Sun-like p modes.
Results. The issues related to parameter extraction on individual p modes discussed here are mode detectability, the detectability and impact of stellar activity cycles, and the ability to measure properties of rotationally split components, which is dependent on the relative importance of the rotational characteristics of the star and the damping of the stochastically excited p modes.
Key words: stars: oscillations / stars: activity / stars: interiors / Sun: helioseismology / methods: data analysis
© ESO, 2008