Automated asteroseismic peak detections

Abstract

Space observatories such as $\text{Kepler}$ have provided data that can potentially revolutionise our understanding of stars. Through detailed asteroseismic analyses we are capable of determining fundamental stellar parameters and reveal the stellar internal structure with unprecedented accuracy. However, such detailed analyses, known as peak bagging, have so far been obtained for only a small percentage of the observed stars while most of the scientific potential of the available data remains unexplored. One of the major challenges in peak bagging is identifying how many solar-like oscillation modes are visible in a power density spectrum. Identification of oscillation modes is usually done by visual inspection which is time-consuming and has a degree of subjectivity. Here, we present a peak detection algorithm specially suited for the detection of solar-like oscillations. It reliably characterises the solar-like oscillations in a power density spectrum and estimates their parameters without human intervention. Furthermore, we provide a metric to characterise the false positive and false negative rates to provide further information about the reliability of a detected oscillation mode or the significance of a lack of detected oscillation modes. The algorithm presented here opens the possibility for detailed and automated peak bagging of the thousands of solar-like oscillators observed by $\text{Kepler}$.

References in corpus (12)

• emcee: The MCMC Hammer
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• Oscillation mode frequencies of 61 main sequence and subgiant stars observed by Kepler
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• Bayesian peak-bagging of solar-like oscillators using MCMC: A comprehensive guide
• Intrinsic photometric characterisation of stellar oscillations and granulation. Solar reference values and CoRoT response functions
• Bayesian peak bagging analysis of 19 low-mass low-luminosity red giants observed with Kepler
• Definitive Sun-as-a-star p-mode frequencies: 23 years of BiSON observations
• Performance of the Birmingham Solar-Oscillations Network (BiSON)
• BiSON data preparation: A correction for differential extinction and the weighted averaging of contemporaneous data

Cited by in corpus (19)

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• TOI-257b (HD 19916b): A Warm sub-Saturn Orbiting an Evolved F-type Star
• The Aarhus red giants challenge II. Stellar oscillations in the red giant branch phase
• Coefficients of variation for detecting solar-like oscillations
• Fast and Automated Peak Bagging with DIAMONDS (FAMED)
• A close-in giant planet escapes engulfment by its star
• Bayesian hierarchical inference of asteroseismic inclination angles
• Unveiling the Structure and Dynamics of Red Giants with Asteroseismology
• Release note: Massive peak bagging of red giants in the Kepler field
• Fast and automated oscillation frequency extraction using Bayesian multi-modality
• KIC 2568888: To be or not to be a binary
• Pushing the boundaries of asteroseismic individual frequency modelling: unveiling two evolved very-low metallicity red giants
• Power density spectra morphologies of seismically unresolved red-giant asteroseismic binaries
• Realising efficient computation of individual frequencies for red-giant models
• Red giant asteroseismic binaries in the Kepler field
• Facing the phase: Gravity-mode offset and buoyancy glitches in red--giant branch stars
• Asteroseismology of iota Draconis and Discovery of an Additional Long-Period Companion
• Hidden oscillations in plain sight: identification of seismically unresolved red-giant asteroseismic binary candidates