Hierarchically modelling Kepler dwarfs and subgiants to improve inference of stellar properties with asteroseismology
With recent advances in modelling stars using high-precision
asteroseismology, the systematic effects associated with our
assumptions of stellar helium abundance (Y) and the mixing-
length theory parameter (α_MLT) are
becoming more important. We apply a new method to improve the
inference of stellar parameters for a sample of Kepler dwarfs
and subgiants across a narrow mass range (0.8 M 1.2
M_⊙). In this method, we include a statistical treatment of
Y and the α_MLT. We develop a
hierarchical Bayesian model to encode information about the
distribution of Y and α_MLT in the
population, fitting a linear helium enrichment law including an
intrinsic spread around this relation and normal distribution in
α_MLT. We test various levels of pooling
parameters, with and without solar data as a calibrator. When
including the Sun as a star, we find the gradient for the
enrichment law, Δ Y / Δ Z =
1.05+0.280.25 and the mean
α_MLT in the population, μ _α =
1.90+0.100.09. While accounting for the
uncertainty in Y and α_MLT, we are still
able to report statistical uncertainties of 2.5 per cent in
mass, 1.2 per cent in radius, and 12 per cent in age. Our method
can also be applied to larger samples that will lead to improved
constraints on both the population level inference and the star-
by-star fundamental parameters.