From Solar-like to Mira stars: a unifying description of stellar pulsators in the presence of stochastic noise
Margarida S. Cunha, Pedro P. Avelino, William J. Chaplin

TL;DR
This paper presents a unified model for stellar pulsations across different star types, explaining power spectral density features and classifying stars based on their pulsation driving mechanisms, with applications to Mira and semiregular variables.
Contribution
The study introduces a comprehensive model that describes stellar pulsations with stochastic noise, unifying different pulsator classes and validating it through numerical simulations and observational data.
Findings
Power spectral density limit approximated by Lorentzian functions.
Classification of stars into stochastic and coherent pulsators.
Scaling relation between mode line width and temperature confirmed.
Abstract
We discuss and characterise the power spectral density properties of a model aimed at describing pulsations in stars from the main-sequence to the asymptotic giant branch. We show that the predicted limit of the power spectral density for a pulsation mode in the presence of stochastic noise is always well approximated by a Lorentzian function. While in stars predominantly stochastically driven the width of the Lorentzian is defined by the mode lifetime, in stars where the driving is predominately coherent the width is defined by the amplitude of the stochastic perturbations. In stars where both drivings are comparable, the width is defined by both these parameters and is smaller than that expected from pure stochastic driving. We illustrate our model through numerical simulations and propose a well defined classification of stars into predominantly stochastic (solar-like) and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
