Bayesian isochrone fitting and stellar ages

TL;DR

This paper introduces a Bayesian framework for quantitatively inferring stellar ages and properties from photometric data, providing a rigorous statistical approach to stellar evolution analysis.

Contribution

It presents a novel Bayesian formalism for stellar age estimation using photometry, incorporating stellar evolution theory as prior information.

Findings

Bayesian method enables age and property estimation with uncertainties.

Application to stellar populations demonstrates the approach's effectiveness.

Framework can be extended to unresolved stellar populations.

Abstract

Stellar evolution theory has been extraordinarily successful at explaining the different phases under which stars form, evolve and die. While the strongest constraints have traditionally come from binary stars, the advent of asteroseismology is bringing unique measures in well-characterised stars. For stellar populations in general, however, only photometric measures are usually available, and the comparison with the predictions of stellar evolution theory have mostly been qualitative. For instance, the geometrical shapes of isochrones have been used to infer ages of coeval populations, but without any proper statistical basis. In this chapter we provide a pedagogical review on a Bayesian formalism to make quantitative inferences on the properties of single, binary and small ensembles of stars, including unresolved populations. As an example, we show how stellar evolution theory can be used in a rigorous way as a prior information to measure the ages of stars between the ZAMS and the Helium flash, and their uncertainties, using photometric data only.