Welcome to gwfast’s documentation!

gwfast is a Python code for forecasting the signal-to-noise ratios and parameter estimation capabilities of networks of gravitational-wave detectors, based on the Fisher information matrix approximation. It is designed for applications to third-generation gravitational-wave detectors. It is based on Automatic Differentiation, which makes use of the library JAX. This allows numerical accuracy, and the possibility to vectorise the computation even on a single CPU, on top of the possibility to parallelise. The code includes a module for parallel computation on clusters.

For further documentation refer to the release papers arXiv:2207.02771 and arXiv:2207.06910.

Package description:

• Installation
• Creating and storing data
• Waveform models
• Single detector analysis
• Detector networks
• Checking, manipulating and inverting the Fisher matrix
• Running script
• Additional definitions

Tutorials:

• gwfast TUTORIAL
• TUTORIAL OF THE NEW FEATURES IMPLEMENTED AFTER arXiv:2207.06910

Available PSDs:

• gwfast/psds

References:

• Citation
• Additional references
• Acknowledgments

Indices and tables

• Index

• Search Page