NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and machine learning techniques. It is a Python library built on JAX.
NetKet is an affiliated project to numFOCUS.
- Homepage: https://www.netket.org
- Citing: https://www.netket.org/cite/
- Documentation: https://netket.readthedocs.io/en/latest/index.html
- Tutorials: https://netket.readthedocs.io/en/latest/tutorials/gs-ising.html
- Examples: https://github.com/netket/netket/tree/master/Examples
- Source code: https://github.com/netket/netket
NetKet runs on MacOS and Linux and requires Python 3.11 or later. We recommend installing NetKet using pip or uv. Do not use conda as JAX has known issues when installed through conda.
pip install --upgrade pip
pip install netketWith GPU support (Linux only):
pip install 'netket[cuda]'Development version:
pip install git+https://github.com/netket/netket.gitFor detailed installation instructions including GPU setup, see our installation guide.
To get started with NetKet, we recommend you give a look at our tutorials page, by running them on your computer or on Google Colaboratory. There are also many example scripts that you can download, run and edit that showcase some use-cases of NetKet, although they are not commented.
If you want to get in touch with us, feel free to open an issue or a discussion here on GitHub, or to join the MLQuantum slack group where several people involved with NetKet hang out. To join the slack channel just accept this invitation