Earl Bellinger's Ph.D. repository on forward and inverse problems in asteroseismology.
If any of these programs are useful to you, please consider citing one or more of the following:
Bellinger, E. P., Angelou, G. C., Hekker, S., Basu, S., Ball, W., Guggenberger, E. (2016). Fundamental Parameters of Main-Sequence Stars in an Instant with Machine Learning. The Astrophysical Journal, 830 (1), 20.
Angelou, G. C., Bellinger, E. P., Hekker, S., Basu, S. (2017). On the Statistical Properties of the Lower Main Sequence. The Astrophysical Journal, 839 (2), 116.
Bellinger, E. P., Angelou, G., Hekker, S., Basu, S., Ball, W., Guggenberger, E. (2017). Fundamental Parameters in an Instant with Machine Learning: Application to Kepler LEGACY Targets. Seismology of the Sun and Distant Stars, European Physical Journal Web of Conferences.
Bellinger, E. P., Basu, S., Hekker, S., Ball, W. (2017). Model-independent Measurement of Internal Stellar Structure in 16 Cygni A and B. The Astrophysical Journal, 851 (2), 80.
See Releases for the versions of this repository corresponding to those papers.
mesa_template/-- directory containing default instructions for a MESA evolutionary track (copied automatically by
python3 sobol_dispatcher.py-- generate initial conditions varied in a quasi-random fashion, calls the following files:
./dispatch.sh-- shell script for generating a parameterized MESA evolutionary track (e.g. -M 1 for a 1 solar mass model)
Rscript discontinuity.R-- detect discontinuities in the simulated evolution
Rscript summarize.R-- summarize an evolutionary track into a matrix
Rscript collate.R-- collect nearly-evenly-spaced points from each summarized simulation into one big data file
simulations.dat; this facilitates the inverse problem
sobol_dispatcher.pywith settings that facilitate comparison with the asteroseismic modeling portal (AMP)
Rscript diffusion.R-- plots the initial and final simulation metallicities as a function of mass and diffusion
Rscript inputs.R-- creates a diagram showing the initial conditions of the grid based off of
../forward/initial_conditions.datwhich is generated by
Random Forest Regression
Rscript tagesstern.R-- degrade BiSON solar frequencies to the level of what is observable from the 16 Cyg stars for the sake of fair evaluation & comparison
Rscript hare_compile.R-- turn the Hare & Hound data into a format I can parse
Rscript perturb.R-- make Monte-Carlo perturbations of solar, Tagesstern, 16 Cyg, kages, and hares data to account for uncertainties in observed data
python3 subsetter.py-- determine the number of evolutionary tracks, models per evolutionary track, and trees in the forest that are needed for
learn.pyto work well
Rscript forest_evaluate.R-- visualize the output of
python3 learn.py-- learn what relates observable data to model properties from
../forward/simulations.datand predict the properties of the stars in
Rscript importances.R-- plots the feature importances of the random forests obtained in
Rscript cyg.R-- plots the predicted quantities of 16 Cyg from
learn.pyagainst literature values
Rscript us-vs-them.R-- plots the predicted quantities of the KAGES stars and the Hare-and-Hound exercise against the literature values; also creates the diffusion plot for the KAGES stars
Rscript legacy.R-- plots the cumulative distribution functions for estimate uncertainties for the LEGACY targets
- Coming soon...
maybe_sub.sh-- shell script for submitting jobs to the condor queuing system
fgong2freqs.sh-- shell script for redistributing a MESA model mesh and calculating adiabatic pulsation frequencies via ADIPLS
seismology.R-- R script for making seismological calculations from a frequencies data file
utils.R-- R utility script for plotting, constants, etc
sobol_lib.py-- python library for generating Sobol (quasi-random) numbers
kerexact.sh-- generates kernel functions from stellar models
Rscript CD_diagram.R-- plot an asteroseismic H-R diagram from a grid of MESA/GYRE models and overplot LEGACY data points on it
python3 plot_sph_harm.py-- make spherical harmonics plots to visualize the pulsation frequencies of solar-like oscillators
python3 plot_grids.py-- make plots of linear, random, and quasi-random (Sobol) grids to justify the use of the latter
python3 plot_classification.py-- make plots of linear and non-linear (in this case, XOR) classification problems to illustrate the limitations and usefulness of basic and advanced ML routines
Rscript 16CygB.R-- make an annotated power spectrum of 16 Cyg B
matlab animate_sph_harm.m-- create animations of spherical harmonics
Rscript interp_vs_reg.R-- plot the difference between linear interpolation and regression
Rscript plot_nearly-even-spacing.R-- show the result of the linear transport problem on finding nearly-evenly spaced points