KIC 4150611: A quadruply eclipsing heptuple star system with a g-mode period-spacing pattern Asteroseismic modelling of the g-mode period-spacing pattern

Abstract

In this work, we aim to estimate the stellar parameters of the primary (Aa) by performing asteroseismic analysis on its period-spacing pattern. We use the C-3PO neural network to perform asteroseismic modelling of the g-mode period-spacing pattern of Aa, discussing the interplay of this information with external constraints from spectroscopy ($T_{\mathrm{eff}}$ and $\log (g)$) and eclipse modelling ($R$). To estimate the level of uncertainty due to different frequency extraction and pattern identification processes, we consider four different variations on the period-spacing patterns. To better understand the correlations between and the uncertainty structure of our parameter estimates, we also employed a classical, parameter-based MCMC grid search on four different stellar grids. The best-fitting, externally constrained model to the period-spacing pattern arrives at estimates of the stellar properties for Aa of: $M=1.51\pm 0.05M_{\odot }$, $X_c=0.43\pm 0.04$, $R=1.66\pm 0.1R_{\odot }$, $f_{\mathrm{ov}}=0.010$, ${\Omega }_c=1.58\pm 0.01$ d${}^{-1}$ with rigid rotation to within the measurement errors, $\log (T_{\mathrm{eff}})=3.856\pm 0.008$ dex, $\log (g)=4.18\pm 0.04$ dex, and $\log (L)=0.809\pm 0.005$ dex, which agree well with previous measurements from eclipse modelling, spectroscopy, and the Gaia DR3 luminosity. We find that the near-core properties of the best-fitting asteroseismic models are consistent with external constraints from eclipse modelling and spectroscopy. Aa appears to be a typical example of a $\gamma$ Dor star, fitting well within existing populations. We find that Aa is quasi-rigidly rotating to within the uncertainties, and note that the asteroseismic age estimate for Aa (1100 $\pm$ 100 Myr) is considerably older than the young (35 Myr) age implied by previous isochrone fits to the B binary in the literature. Our MCMC parameter-based grid-search agrees well with our pattern-modelling approach.

Accepted, A&A

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Cited by in corpus (1)

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