Bayesian frequency analysis of HD 201433 observations with BRITE

TL;DR

This paper introduces a Bayesian method for analyzing closely spaced frequencies in time series data, demonstrated on BRITE photometry of HD 201433, revealing nine significant rotationally split dipole modes.

Contribution

A new automated Bayesian approach for detecting and assessing close frequencies in time series data, improving frequency analysis accuracy.

Findings

Identified nine statistically significant rotationally split dipole modes in HD 201433

Validated the method with synthetic data sets

Enhanced frequency resolution in stellar oscillation analysis

Abstract

Multiple oscillation frequencies separated by close to or less than the formal frequency resolution of a data set are a serious problem in the frequency analysis of time series data. We present a new and fully automated Bayesian approach that searches for close frequencies in time series data and assesses their significance by comparison to no signal and a mono-periodic signal. We extensively test the approach with synthetic data sets and apply it to the 156 days-long high-precision BRITE photometry of the SPB star HD 201433, for which we find a sequence of nine statistically significant rotationally split dipole modes.