Inferring coupling strengths of mixed-mode oscillations in red-giant stars using deep learning

TL;DR

This paper introduces a neural network that rapidly infers the coupling strength of mixed modes in red-giant stars, providing insights into stellar interiors and evolution with improved accuracy over existing methods.

Contribution

The study develops a deep learning approach to accurately estimate coupling strength in red-giant stars, outperforming traditional techniques and aligning better with stellar evolution models.

Findings

Neural network infers coupling strength in ~5 ms.

Approximately 43% of inferences agree within 0.03 of other methods.

Decline in coupling strength on the red-giant branch is steeper than previously thought.

Abstract

Asteroseismology is a powerful tool that may be applied to shed light on stellar interiors and stellar evolution. Mixed modes, behaving as acoustic waves in the envelope and buoyancy modes in the core, are remarkable because they allow for probing the radiative cores and evanescent zones of red-giant stars. Here, we have developed a neural network that can accurately infer the coupling strength, a parameter related to the size of the evanescent zone, of solar-like stars in $\sim$5 milliseconds. In comparison with existing methods, we found that only $\sim$43\% inferences were in agreement to within a difference of 0.03 on a sample of $\sim$1,700 \textit{Kepler} red giants. To understand the origin of these differences, we analyzed a few of these stars using independent techniques such as the Monte Carlo Markov Chain method and Echelle diagrams. Through our analysis, we discovered that these alternate techniques are supportive of the neural-net inferences. We also demonstrate that the network can be used to yield estimates of coupling strength and large period separation in stars with structural discontinuities. Our findings suggest that the rate of decline in the coupling strength in the red-giant branch is greater than previously believed. These results are in closer agreement with calculations of stellar-evolution models than prior estimates, further underscoring the remarkable success of stellar-evolution theory and computation. Additionally, we show that the uncertainty in measuring large-period separation increases rapidly with diminishing coupling strength.