https://github.com/netket/netket
Machine learning algorithms for many-body quantum systems
https://github.com/netket/netket
complex-neural-network deep-learning exact-diagonalization hamiltonian jax machine-learning machine-learning-algorithms markov-chain-monte-carlo monte-carlo-methods neural-networks physics-simulation quantum quantum-state-tomography unitaryhack variational-method variational-monte-carlo
Last synced: 22 days ago
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Machine learning algorithms for many-body quantum systems
- Host: GitHub
- URL: https://github.com/netket/netket
- Owner: netket
- License: apache-2.0
- Created: 2018-04-23T18:48:08.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2024-10-28T09:54:25.000Z (about 1 year ago)
- Last Synced: 2024-10-28T21:48:21.297Z (about 1 year ago)
- Topics: complex-neural-network, deep-learning, exact-diagonalization, hamiltonian, jax, machine-learning, machine-learning-algorithms, markov-chain-monte-carlo, monte-carlo-methods, neural-networks, physics-simulation, quantum, quantum-state-tomography, unitaryhack, variational-method, variational-monte-carlo
- Language: Python
- Homepage: https://www.netket.org
- Size: 63.6 MB
- Stars: 542
- Watchers: 26
- Forks: 188
- Open Issues: 100
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATIONS.bib
Awesome Lists containing this project
- quantum-awesome - https://github.com/netket/netket
- awesome-jax - NetKet - Machine Learning toolbox for Quantum Physics. <img src="https://img.shields.io/github/stars/netket/netket?style=social" align="center"> (Libraries)
README
# __NetKet__
[](https://numfocus.org)
[](https://github.com/netket/netket/releases)
[](https://scipost.org/SciPostPhysCodeb.7/pdf)
[](https://codecov.io/gh/netket/netket)
[](https://join.slack.com/t/mlquantum/shared_invite/zt-19wibmfdv-LLRI6i43wrLev6oQX0OfOw)
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](https://github.com/google/jax).
NetKet is an affiliated project to [numFOCUS](https://numfocus.org).
- **Homepage:**
- **Citing:**
- **Documentation:**
- **Tutorials:**
- **Examples:**
- **Source code:**
## Installation and Usage
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.
```sh
pip install --upgrade pip
pip install netket
```
**With GPU support (Linux only):**
```sh
pip install 'netket[cuda]'
```
**Development version:**
```sh
pip install git+https://github.com/netket/netket.git
```
For detailed installation instructions including GPU setup, see our [installation guide](https://netket.readthedocs.io/en/latest/install.html).
## Getting Started
To get started with NetKet, we recommend you give a look at our [tutorials page](https://netket.readthedocs.io/en/latest/tutorials/gs-ising.html), by running them on your computer or on [Google Colaboratory](https://colab.research.google.com).
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](https://join.slack.com/t/mlquantum/shared_invite/zt-19wibmfdv-LLRI6i43wrLev6oQX0OfOw)
## License
[Apache License 2.0](https://github.com/netket/netket/blob/master/LICENSE)