fiesta documentation#
Fast Inference of Electromagnetic Signals and Transients with jAx.
fiesta is a JAX-based Python library for training machine-learning surrogates for
kilonova and gamma-ray burst afterglow models, and for performing fast Bayesian inference
on photometric lightcurve data from astronomical transients.
Recently, some analytical models have also been made availabe that can be used for light curve fitting.
Note
Documentation is work in progress! Some sections may be incomplete or under active development. We appreciate your patience as we improve the documentation. Please contact us with any questions or issues you might encounter.
How to install the package.
Learn about the two types of surrogate models (FluxModel and LightcurveModel) and how to load built-in and custom surrogates.
How to prepare training data and train your own surrogate models.
How to perform Bayesian light curve fitting using the fiesta functionalities.
Full auto-generated API documentation for all modules.
If you use fiesta, consider citing our paper 📝