Bayesian Optimisation for the Characterisation of Mixed Modes.
Execute the following to your base directory of choice:
git clone https://github.com/jsk389/BOChaMM.gitpeakbag/-- Contains the peakbagged modes for all red giants examined in our study.notebooks/-- Contains two notebooks detailing our method of measuring mixed-mode parameters. Visit these to learn how to use our data products and code.results/images/-- Contains plots of stretched echelle diagrams of our fits.results/samples/-- Contains samples from the Bayesian optimizer for the forward modelling step. See the notebooks on how to use these.results/tables/-- Summary of results from the paper.
Due to the large volume of the data products (peakbagged modes, BayesOpt samples, etc.), we have migrated the full dataset to Zenodo, with a few examples in the existing repo folders. Get the full data here.
The following schematic demonstrates the optimization procedures involved in BoCHaMM.
BOChaMM uses the TuRBO algorithm for optimization, with a quick preview on how it applies to the PSxPS task shown in the following:
- High-level version of notebooks
- Notebook for producing plots in paper
- Proper import to
sloscillationsrepo - Package code and make docs
- Binder notebooks
Paper upcoming and in review!