Precise Time-Domain Asteroseismology and a Revised Target List for TESS Solar-Like Oscillators

TL;DR

This paper introduces a time-domain modeling approach for asteroseismology of TESS data, improving measurement accuracy and enabling detection of marginal oscillations in solar-like stars.

Contribution

It presents a novel time-domain method using Gaussian Process kernels for analyzing TESS asteroseismic data, enhancing detection sensitivity and accuracy.

Findings

Time-domain modeling nearly doubles { u}max measurement accuracy.

Revised detection probabilities increase the number of recoverable marginal detections.

Software tool provided for calculating detection probabilities for various targets.

Abstract

The TESS mission has provided a wealth of asteroseismic data for solar-like oscillators. However, these data are subject to varying cadences, large gaps, and unequal sampling, which complicates analysis in the frequency domain. One solution is to model the oscillations in the time domain by treating them as stochastically damped simple harmonic oscillators through a linear combination of Gaussian Process kernels. We demonstrate this method on the well-studied subgiant star nu Indi and a sample of Kepler red giant stars observed by TESS, finding that the time domain model achieves an almost two-fold increase in accuracy for measuring {\nu}max compared to typical frequency domain methods. To apply the method to new detections, we use stellar parameters from Gaia DR3 and the TESS input catalog to calculate revised asteroseismic detection probabilities for all TESS input catalog targets with T<12 mag and a predicted {\nu}max>240{\mu}Hz. We also provide a software tool to calculate detection probabilities for any target of interest. Using the updated detection probabilities we show that time-domain asteroseismology is sensitive enough to recover marginal detections, which may explain the current small number of frequency-based detections of TESS oscillations compared to pre-flight expectations.