Institution: Embry-Riddle Aeronautical University
Title: Precise Stellar Properties via Bayesian Analysis of Stellar Evolution
Abstract: While it is well known that astronomers can use stellar models to infer the ages of open and globular clusters, as well as populations of white dwarfs, what is often not appreciated is that with precision astrometry and photometry, we can frequently infer the ages of individual stars. Individual stellar ages are themselves valuable, for instance for exoplanet host stars, and these individual stellar ages can be aggregated for stellar population studies. I will discuss our Bayesian approach to comparing stellar evolution models to data to infer stellar ages, and also speak briefly about how this approach can be used to derive highly precise stellar cluster properties, infer binary mass ratios, and even study multi-component globular clusters. My group’s BASE-9 code, upon which this work is based, is open-source and available on GitHub, and for those interested in incorporating it into their research, we are happy to provide training and support.
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