Analysing solar-like oscillations with an automatic pipeline

TL;DR

This paper presents an automated pipeline for analyzing solar-like oscillations in stars, designed to handle large datasets from Kepler by identifying p-mode frequencies and characteristics efficiently.

Contribution

The paper introduces a new automated analysis pipeline for solar-like oscillations, enabling scalable processing of Kepler data without individual star analysis.

Findings

Pipeline successfully identifies p-mode frequency ranges.

Accurate estimation of mode amplitudes and large separation.

Validated on synthetic AsteroFLAG data.

Abstract

Kepler mission will provide a huge amount of asteroseismic data during the next few years, among which hundreds of solar-like stars will be targeted. The amount of stars and their observation length represent a step forward in the comprehension of the stellar evolution that has already been initiated by CoRoT and MOST missions. Up to now, the slow cadence of observed targets allowed an individual and personalized analysis of each star. During the survey phase of Kepler, this will be impossible. This is the reason why, within the AsteroFLAG team, we have been developing automatic pipelines for the Kepler solar-like oscillation stars. Our code starts by finding the frequency-range where p-mode power is present and, after fitting the background, it looks for the mode amplitudes as well as the central frequency of the p-mode hump. A good estimation of the large separation can thus be inferred in this region. If the signal to noise is high enough, the code obtains the characteristics of the p modes by doing a global fitting on the power spectrum. Here, we will first describe a few features of this pipeline and its application to AsteroFLAG synthetic data to check the validity of the code.