plane-wave_pinns

Physics-informed neural networks for solving a system of coupled oscillators using randomised boundary conditions during training

https://github.com/r-clem/plane-wave_pinns

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (5.0%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Physics-informed neural networks for solving a system of coupled oscillators using randomised boundary conditions during training

Basic Info
  • Host: GitHub
  • Owner: R-Clem
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 22.5 KB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created 7 months ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

Physics-informed neural networks (PINNs) for solving a system of two coupled oscillators.

Both scripts allow for training over a normal distribution of randomly-sampled boundary conditions in order to decouple the trained PINN from a unique solution. The conventional PINN script is present to demonstrate that this tends not to work very well for conventional activation functions such as tanh. The plane-wave PINN script creates and trains a PINN that learns a general solution that is only made unique during the evaluation of the network, when a set of boundary conditions and time are passed to it.

The code in this repository was used to generate the results for the paper "Plane-Wave Decomposition and Randomised Training; a Novel Path to Generalised Physics Informed Neural Networks for Simple Harmonic Motion" and is available on arXiv: arXiv:2504.00249v3

Owner

  • Login: R-Clem
  • Kind: user

Citation (CITATION.cff)

@software{ClementsPWPINNs2025,
  author = {Clements, Rory},
  month = {7},
  title = {{Plane wave PINNs for coupled oscillators}},
  howpublished = {\url{https://github.com/R-Clem/Plane-wave_PINNs}},
  version = {1.0.0},
  year = {2025}
}

GitHub Events

Total
  • Push event: 2
  • Commit comment event: 1
Last Year
  • Push event: 2
  • Commit comment event: 1

Dependencies

python_requirements.txt pypi
  • Jinja2 ==3.1.6
  • MarkupSafe ==3.0.2
  • PyQt5 ==5.15.11
  • PyQt5-Qt5 ==5.15.17
  • PyQt5_sip ==12.17.0
  • contourpy ==1.3.2
  • cycler ==0.12.1
  • filelock ==3.18.0
  • fonttools ==4.58.1
  • fsspec ==2025.5.1
  • kiwisolver ==1.4.8
  • matplotlib ==3.10.3
  • mpmath ==1.3.0
  • networkx ==3.5
  • numpy ==2.2.6
  • nvidia-cublas-cu12 ==12.6.4.1
  • nvidia-cuda-cupti-cu12 ==12.6.80
  • nvidia-cuda-nvrtc-cu12 ==12.6.77
  • nvidia-cuda-runtime-cu12 ==12.6.77
  • nvidia-cudnn-cu12 ==9.5.1.17
  • nvidia-cufft-cu12 ==11.3.0.4
  • nvidia-cufile-cu12 ==1.11.1.6
  • nvidia-curand-cu12 ==10.3.7.77
  • nvidia-cusolver-cu12 ==11.7.1.2
  • nvidia-cusparse-cu12 ==12.5.4.2
  • nvidia-cusparselt-cu12 ==0.6.3
  • nvidia-nccl-cu12 ==2.26.2
  • nvidia-nvjitlink-cu12 ==12.6.85
  • nvidia-nvtx-cu12 ==12.6.77
  • packaging ==25.0
  • pillow ==11.2.1
  • pyparsing ==3.2.3
  • python-dateutil ==2.9.0.post0
  • scipy ==1.15.3
  • setuptools ==80.9.0
  • six ==1.17.0
  • sympy ==1.14.0
  • torch ==2.7.0
  • torchaudio ==2.7.0
  • torchvision ==0.22.0
  • triton ==3.3.0
  • typing_extensions ==4.14.0