Stellar models for "A prescription for the asteroseismic surface correction" by Li, Yaguang et al. (2023)

This folder publishes the stellar models utilized in Li et al. (2023)

The stellar models presented here encompass a range of parameters: mass (0.7, 2.3) solar mass, Yinit (0.22, 0.32), [M/H] within (-0.94, 0.56) dex, and amlt (1.3, 2.7). All evolutionary tracks are calculated up to the point on the RGB when the p-mode large separtion Dnu equals 2 muHz.

Each model entry (row) are presented with classical observables (Teff, radius, luminosity, ...) and radial modes (mode_freq, mode_inertia, mode_n, ...)

For a comprehensive description of the stellar models, please refer to the paper.

The folder contains three sets of stellar models. These models are stored in the "npy" format. They can be read in Python using the following code: "import numpy as np; data = np.load(filename, allow_pickle=True);"

- grid_models_surface_effect_corrected/tracks*.npy

This set includes stellar models with frequencies that have surface effect removed.

- grid_models_surface_effect_uncorrected/tracks*.npy

This set includes stellar models with frequencies in the original uncorrected format.

- stats_models_for_fDnu_ANN_weights.npy

This file is a statistical stellar model fitted by an artificial neural network with fully connected layers. It can be used for calculating fDnu, the correction factor of the Dnu scaling relation, or for doing any stellar parameter inference using global parameters (such as numax, Dnu, Teff, lum, etc.). More details and example use cases can be found at https://github.com/parallelpro/surface/