The Power of Principled Bayesian Methods in the Study of Stellar Evolution

Authors

Ted von Hippel, Embry-Riddle Aeronautical UniversityFollow
David van Dyk, Imperial College LondonFollow
David Stenning, University of CaliforniaFollow
Elliot Robinson, Argiope Technical SolutionsFollow
Elizabeth Jeffery, James Madison UniversityFollow
Nathan Stein, University of PennsylvaniaFollow
William Jefferys, University of TexasFollow
Erin M. O'Malley, Siena College; Dartmouth CollegeFollow

Submitting Campus

Daytona Beach

Department

Physical Sciences

Document Type

Article

Publication/Presentation Date

11-14-2014

Abstract/Description

It takes years of effort employing the best telescopes and in- struments to obtain high-quality stellar photometry, astrometry, and spectroscopy. Stellar evolution models contain the experience of life- times of theoretical calculations and testing. Yet most astronomers fit these valuable models to these precious datasets by eye. We show that a principled Bayesian approach to fitting models to stellar data yields substantially more information over a range of stellar astrophysics. We highlight advances in determining the ages of star clusters, mass ratios of binary stars, limitations in the accuracy of stellar models, post-main-sequence mass loss, and the ages of individual white dwarfs. We also outline a number of unsolved problems that would benefit from principled Bayesian analyses.

Publication Title

EAS Publications Series

DOI

https://doi.org/10.1051/eas/1465007

Publisher

EDP Science

Scholarly Commons Citation

von Hippel, T., van Dyk, D., Stenning, D., Robinson, E., Jeffery, E., Stein, N., Jefferys, W., & O'Malley, E. M. (2014). The Power of Principled Bayesian Methods in the Study of Stellar Evolution. EAS Publications Series, 65(). https://doi.org/10.1051/eas/1465007