Welcome to mlgw_bns’s documentation!

The purpose of the mlgw_bns package is to speed up the generation of gravitational waveforms for binary neutron star mergers, by training a machine learning model on effective-one-body waveforms.

The code can be found on the github page.

Contact

• Contact

Explanation

• Higher order modes
  • Spherical harmonics
  • The time-domain 22 wave
  • Frequency-domain waves

Usage guides

• Installation
  • From pip
  • From the repo
  • Testing and dev functionality
• Overview
  • Making a new model
• Profiling the model evaluation
• Validating the waveforms’ accuracy
• Optimizing hyperparameters

Package reference

• Model for waveform generation
• Management of a training and validation dataset
• Multibanding
• Downsampling and interpolation
• Data management
• Principal Component Analysis
• Neural Network
• Hyperparameter Optimization
• Model Validation
• Fixed Dataset Training

Indices and tables

• Index

• Module Index