NetKet: The Machine Learning Toolbox for Quantum Physics

NetKet: The Machine Learning Toolbox for Quantum Physics#

NetKet is a Python library for using machine learning methods to study many-body quantum systems. It provides efficient and flexible building blocks for writing novel algorithms as well as simple, easy-to-use implementations of established algorithms.

NetKet is built on top of JAX, a framework for differentiable programming that works on CPUs, GPUs and TPUs. Neural Network architectures can be specified using any JAX-based framework such as Flax.

💻 Installation

Get NetKet up and running on your system

Installation
🚀 Getting started

Learn NetKet with hands-on tutorials

Ground-State: Ising model
📚 User guides

In-depth guides for NetKet components

In-depth guides
🔬 Examples

Short runnable scripts showcasing features

https://github.com/netket/netket/tree/master/Examples

Supporting and Citing#

The software in this ecosystem was developed as part of academic research. If you would like to help support it, please star the repository as such metrics may help us secure funding in the future. If you use NetKet software as part of your research, teaching, or other activities, we would be grateful if you could cite our work.

Guidelines on citation are provided in the Citing section of our website.