mlgw_bns

Contact

  • Contact

Explanation

  • Higher order modes
  • Precession: the twist and its conventions

Usage guides

  • Installation
  • Overview
  • Profiling the model evaluation
  • Validating the waveforms’ accuracy
  • Optimizing hyperparameters
  • Training at scale on a SLURM cluster

Package reference

  • Model for waveform generation
  • Batched, per-mode evaluation (numpy and JAX)
  • Single-mode model
  • Management of a training and validation dataset
  • Multibanding
  • Downsampling and interpolation
  • Data management
  • Principal Component Analysis
  • Neural Network
  • Hyperparameter Optimization
  • Precessing waveforms
  • Model Validation
  • Fixed Dataset Training
  • Training at scale
mlgw_bns
  • Overview: module code

All modules for which code is available

  • mlgw_bns.batched
  • mlgw_bns.batched_precession
  • mlgw_bns.data_management
  • mlgw_bns.dataset_generation
  • mlgw_bns.downsampling_interpolation
  • mlgw_bns.fixed_dataset_training
  • mlgw_bns.hyperparameter_optimization
  • mlgw_bns.jax_mlp
  • mlgw_bns.mode_model
  • mlgw_bns.model
  • mlgw_bns.model_files
  • mlgw_bns.model_validation
  • mlgw_bns.modes_dataset
  • mlgw_bns.multibanding
  • mlgw_bns.neural_network
  • mlgw_bns.precessing_model
  • mlgw_bns.principal_component_analysis
  • mlgw_bns.sharding
  • mlgw_bns.special_func
  • mlgw_bns.spin_conversion
  • mlgw_bns.twist_waveform

© Copyright 2021, Jacopo Tissino.

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