Asteroseismology with PBjam 2.0: measuring dipole mode frequencies in coupling regimes from main sequence to low-luminosity red giant stars

TL;DR

PBjam 2.0 is an open-source tool that automatically measures dipole mode frequencies in stars across different evolutionary stages, improving stellar modeling by handling complex p- and g-mode couplings.

Contribution

The paper introduces three new models in PBjam 2.0 for identifying $ ext{l}=1$ modes in stars with varying p- and g-mode coupling, extending its applicability.

Findings

Successfully models $ ext{l}=1$ modes in main-sequence, sub-giant, and red giant stars.

Uses Bayesian methodology with nonparametric priors for robust mode identification.

Enhances the capability of PBjam to analyze a broader range of stellar oscillations.

Abstract

PBjam is an open-source software package for measuring mode frequencies of solar-like oscillators. These frequencies help constrain stellar evolution models to precisely estimate masses, radii, and ages of stars. The overall aim of PBjam is to simplify this process to the point where it may be done by non-experts or performed on thousands of stars with minimal interaction. The initial release of PBjam was restricted to only identifying modes of $\ell=0$ and $\ell=2$, since these are the simplest to treat consistently across different stellar evolutionary stages. Here we introduce a new set of three separate models which lets PBjam automatically identify $\ell=1$ modes in stars that experience varying degrees of coupling between p- and g-modes. These include a simple asymptotic relation for p-modes which can be applied to main-sequence stars, a matrix formalism aimed at treating frequency dependent coupling in sub-giants, and a uniform coupling model which is suitable for red giants. These models follow the Bayesian methodology established in the first release of PBjam, where a large set of previous observations is used to construct a nonparametric prior probability density for the new set of model parameters. This extension allows PBjam to build a more complete description of the power due to oscillations across a wider range of evolutionary stages.