2018
DOI: 10.3847/1538-4365/aaccfb
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Forward Asteroseismic Modeling of Stars with a Convective Core from Gravity-mode Oscillations: Parameter Estimation and Stellar Model Selection

Abstract: We propose a methodological framework to perform forward asteroseismic modeling of stars with a convective core, based on gravity-mode oscillations. These probe the near-core region in the deep stellar interior. The modeling relies on a set of observed high-precision oscillation frequencies of lowdegree coherent gravity modes with long lifetimes and their observational uncertainties. Identification of the mode degree and azimuthal order is assumed to be achieved from rotational splitting and/or from period spa… Show more

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Cited by 105 publications
(177 citation statements)
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References 159 publications
(262 reference statements)
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“…These parameters were chosen as 'reasonable' for our targets; a full investigation of the influence of each parameter is beyond the scope of this paper. Interested readers are directed to Aerts et al (2018) and references therein. The tracks were computed for the mass range 1.0-3.0 M , at intervals of 0.05 M , and include T eff , log L, log g and age at 600 steps.…”
Section: Calculation Of Evolutionary Tracksmentioning
confidence: 99%
“…These parameters were chosen as 'reasonable' for our targets; a full investigation of the influence of each parameter is beyond the scope of this paper. Interested readers are directed to Aerts et al (2018) and references therein. The tracks were computed for the mass range 1.0-3.0 M , at intervals of 0.05 M , and include T eff , log L, log g and age at 600 steps.…”
Section: Calculation Of Evolutionary Tracksmentioning
confidence: 99%
“…This requires dedicated asteroseismic modelling tools suitable to interpret the measured frequencies. Here, we explore and apply aspects of the methodology developed specifically for gravito-inertial modes by Aerts et al (2018). We first highlight relevant properties of the asteroseismic grids upon which we rely and subsequently exploit the probing power of the three observables (Π 0 , T eff , log g).…”
Section: Gravity-mode Period Spacingsmentioning
confidence: 99%
“…Such criteria exists from information theory and we used the Bayesian information criterion (BIC; Schwarz 1978) to select the best model for each target. This criteria aims to infer the model that fits the data the best without over fitting and is used in several studies of stellar physics to infer the most likely model that reproduce the data from a set of different models (e.g., Degroote et al 2009;Aerts et al 2018;Matrà et al 2019). The BIC criteria was developped for model inference and is more conservative in the choice of the most likely model (higher penalty for models with more parameters to fit) than the Akaike information criterion (AIC) that was developed for prediction purposes.…”
Section: Strategymentioning
confidence: 99%
“…However, the differences between the BIC values for a given dataset can be small and several models can be considered. Usually, models with a difference of more than 10 with the BIC of the best model can be ruled out whereas a difference between 10 and 6 can be considered as moderately strong evidence for the best model, between 6 and 2 as positive evidence in favour of the best model and less than 2 as weak evidence (e.g., Aerts et al 2018).…”
Section: Strategymentioning
confidence: 99%