An in-depth study of grid-based asteroseismic analysis
Ning Gai, Sarbani Basu, William J. Chaplin, Yvonne Elsworth

TL;DR
This study thoroughly examines grid-based asteroseismic analysis methods, revealing their precision, biases, and dependencies, especially emphasizing the importance of metallicity knowledge for accurate stellar parameter estimation.
Contribution
It provides a detailed assessment of errors, biases, and correlations in grid-based asteroseismic analysis, highlighting the conditions for accurate stellar parameter determination.
Findings
Radii can be measured with high precision using grid-based methods.
Biases in measurements can be minimized with known metallicity.
Log g can be accurately determined with minimal model dependence.
Abstract
NASA's Kepler mission is providing basic asteroseismic data for hundreds of stars. One of the more common ways of determining stellar characteristics from these data is by so-called "grid based" modelling. We have made a detailed study of grid-based analysis techniques to study the errors (and error-correlations) involved. As had been reported earlier, we find that it is relatively easy to get very precise values of stellar radii using grid-based techniques. However, we find that there are small, but significant, biases that can result because of the grid of models used. The biases can be minimized if metallicity is known. Masses cannot be determined as precisely as the radii, and suffer from larger systematic effects. We also find that the errors in mass and radius are correlated. A positive consequence of this correlation is that log g can be determined both precisely and accurately…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
