MIST White Dwarf Cooling Data Files

This repository contains the white dwarf cooling tracks and cooling age contours associated with the paper MESA Isochrones and Stellar Tracks (MIST) III. The White Dwarf Cooling Sequence. The included files are

• default_grids_scaled_solar.tgz, a grid of all WD cooling tracks and contours for the solar-scaled metallicity [α/Fe] = 0 models from MIST v2, descended from the default model grid which includes rotation. This includes directories for metallicities ranging from [Fe/H] = -4 to [Fe/H] = +0.5, with a total of 1360 WD cooling tracks.
• default_grids_full.tgz, a grid of all WD cooling tracks and contours for all [α/Fe] values from MIST v2, descended from the default model grid which includes rotation.
• nonrotating_grids_full.tgz, a grid of all WD cooling tracks and contours for all [α/Fe] values from MIST v2, descended from the non-rotating model grid.
• BC_tables.tgz, tables of bolometric corrections for pure-hydrogen atmosphere white dwarfs for all of the filter sets included in MIST, based on the synthetic model spectra of Tremblay et al (2011).
• example.py, a python script that shows how to load in WD tracks and contours, select desired filters, interpolate magnitudes based on the files from BC_tables, and plot the Gaia color-magnitude diagram for these tracks and contours.
• Example_GaiaCMD_feh_p000_afe_p0.png, example Gaia CMD produced by example.py for the WD models descended from solar-metallicity progenitors, found in default_grids_scaled_solar/feh_p000_afe_p0_wds_vvcrit0.4

Unless you specifically want to investigate the effects of varying [α/Fe] in the WD progenitor models, you can probably obtain more than enough WD cooling data just by downloading the data in default_grids_scaled_solar.tgz. The reason for the "default" and "nonrotating" data files is that MIST includes grids for both rotating and non-rotating progenitor stars to the WDs. As described in the MIST papers, the default rotating grid is initialized at v/vcrit = 0.4 for stars with initial masses above 1.8 Msun, while rotation is ramped down to zero for stars below 1.2 Msun. Due to angular momentum transport, the WDs ultimately produced by these rotating model grids are still fairly slowly rotating, with rotation periods on the order of several hours to a few days.

You can find the full MESA setup for running these models in the companion zenodo repository: https://doi.org/10.5281/zenodo.15196933.

Data File Contents

The cooling contour files (*.wdcool and *.rawcool) contain the following columns for quantities along contours of constant WD cooling age:

log_age  log_L  log_Teff  log_R  log_g  Mass  log_M_H  log_M_He

The log_age column from the contour files spans from 6.0 to 10.3 in steps of 0.05, and the example.py script shows how to mask the arrays based on that column to select a contour at a particular age value. The cooling track files contain the following columns:

log_cool_age log_tot_age log_L log_Teff log_R log_g log_MH log_MHe log_Mcvz log_Tc log_Rhoc

The cool_age column is for WD cooling age, and the tot_age column is for total age of the model from ZAMS. Note that the outer convection zone mass (log_Mcvz) is only reported when it has developed to a thickness of log(Mcvz/MWD) > -11, so these tracks do not fully resolve or report the onset of convection for very thin convection zones.

Example Usage

You can reproduce the Gaia CMD plot included in this repository in a few simple steps. First, download default_grids_scaled_solar.tgz, BC_tables.tgz, and example.py to the same directory. Then, in that directory, run the following commands:

tar xvzf default_grids_scaled_solar.tgz && rm default_grids_scaled_solar.tgz
tar xvzf BC_tables.tgz && rm BC_tables.tgz
cd default_grids_scaled_solar/feh_p000_afe_p0_wds_vvcrit0.4
cp ../../example.py .
python example.py

This should produce a png file named GaiaCMD.png that looks like the example png included in this repository. This plots a subset of the tracks and all of the (smoothed) cooling contours for the solar-metallicity (feh_p000_afe_p0) WD grid. The non-smoothed cooling contours can be found in the *.rawcool files as opposed to the *.wdcool files.

The key piece of code for converting from theoretical tracks to colors and magnitudes is this simple function for loading in the relevant table from one of the bolometric correction files and then interpolating the BC for the desired filter as a function of logg and logTeff.

def BC_Tremblay(logg_in,logTeff_in,filename,filtername,interp_kind='cubic',bderr=True):
    BCtable = np.genfromtxt(filename,skip_header=5,names=True)
    Teff = BCtable['Teff'][::7]
    logg = BCtable['logg'][:7]
    filter_table = BCtable[filtername].reshape(len(Teff),len(logg))
    interp_table = RegularGridInterpolator((Teff,logg),filter_table,
                                           bounds_error=bderr,method=interp_kind)
    return interp_table((10**logTeff_in,logg_in))

For example, to get the bolometric correction for the Gaia G band at log(g) = 8.0, Teff = 10,000 K, you can call this function as

BC_GaiaG = BC_Tremblay(8.0,4.0,'Tremblay.UBVRIplus','Gaia_G_EDR3')

Or you can call this function on arrays of logg and logTeff to get bolometric corrections along tracks or contours, as demonstrated in example.py.

How to Cite

When using the WD cooling model data, please cite the following paper:

Bauer et al. 2025, ApJS accepted

When using the bolometric correction tables to calculate colors and magnitudes, please cite the following paper in addition to the above:

Tremblay et al. 2011, ApJ, 730, 128