Using the Gaia Excess Uncertainty as a Proxy for Stellar Variability and Age

Abstract

Stars are known to be more active when they are young, resulting in a strong correlation between age and photometric variability. The amplitude variation between stars of a given age is large, but the age–variability relation becomes strong over large groups of stars. We explore this relation using the excess photometric uncertainty in Gaia photometry (VarG, VarBP, and VarRP) as a proxy for variability. The metrics follow a Skumanich-like relation, scaling as ≃t −0.4. By calibrating against a set of associations with known ages, we show how the Var of population members can predict group ages within 10%–20% for associations younger than ≃2.5 Gyr. In practice, age uncertainties are larger, primarily due to the finite group size. The index is most useful at the youngest ages (<100 Myr), where the uncertainties are comparable to or better than those derived from a color–magnitude diagram (CMD). The index is also widely available, easy to calculate, and can be used at intermediate ages where there are few or no pre- or post-main-sequence stars. We further show how Var can be used to find new associations and test if a group of comoving stars is a real coeval population. We apply our methods to Theia groups within 350 pc and find ≳90% are inconsistent with drawing stars from the field and ≃80% have variability ages consistent with those derived from the CMD. Our findings suggest the great majority of these groups contain real populations.

Stellar variability in Gaia DR3

“…On the other hand, stars that are clearly in the PMS are concentrated in the last three bins, with only a few stars in the first bin. Furthermore, the fraction of objects in the third and fourth (s G > 50 mmag) bins is higher in the two youngest clusters (Villafranca O-026 and Villafranca O-016, PMS ages of ∼2 Ma and ∼4 Ma, respectively) than in the two oldest clusters (Villafranca O-021 and Villafranca O-024, PMS ages of ∼5 Ma and ∼8 Ma, respectively), indicating an age effect in the sense that variability decreases with age (see also Barber & Mann 2023).…”

“…The quality and quantity of information provided by Gaia allows for a limited analysis of photometric variability without the use of light curves but based instead on the observed photometric dispersions. Previous papers have done that (Deason et al 2017;Belokurov et al 2017;Iorio et al 2018;Vioque et al 2020;Guidry et al 2021;Mowlavi et al 2021;Andrew et al 2021;Barlow et al 2022;Barber & Mann 2023) but they have not exploited the full potential provided by using a large fraction of the Gaia DR3 sample, as some of those use previous data releases and others use relatively small samples. That is the purpose of this paper: to calculate astrophysical photometric dispersions for the majority of Gaia DR3 objects with G ≤ 17 mag.…”