BAFFLES: Bayesian Ages for Field Lower-Mass Stars

TL;DR

BAFFLES is a Bayesian framework that estimates stellar ages and uncertainties using calcium emission and lithium abundance data, improving age determination for field stars.

Contribution

It introduces a robust Bayesian method to derive age posteriors for stars based on empirical likelihood functions from benchmark clusters.

Findings

Consistent age posteriors with literature values.

Applied to over 2630 stars with compiled data.

Provides a probabilistic age estimate with uncertainty.

Abstract

Age is a fundamental parameter of stars, yet in many cases ages of individual stars are presented without robust estimates of the uncertainty. We have developed a Bayesian framework, BAFFLES, to produce the age posterior for a star from its calcium emission strength (log($R'_{HK}$)) or lithium abundance (Li EW) and $B-V$ color. We empirically determine the likelihood functions for calcium and lithium as functions of age from literature measurements of stars in benchmark clusters with well-determined ages. We use a uniform prior on age which reflects a uniform star formation rate. The age posteriors we derive for several test cases are consistent with literature ages found from other methods. BAFFLES represents a robust method to determine the age posterior probability distribution for any field star with $0.45 \leq B-V \leq 0.9$ and a measurement of $R'_{HK}$ and/or $0.35 \leq B-V \leq 1.9$ and measured Li EW. We compile colors, $R'_{HK}$, and Li EW from over 2630 nearby field stars from the literature and present the derived BAFFLES age posterior for each star.