Graphix

An open-source Python library for building, optimizing, and simulating measurement-based quantum computations (MBQC). Develop your MBQC workflow with the help of our modular, extensible, and user-friendly software framework.

Why Graphix?

Whether you are learning MBQC, developing protocols and algorithms, or testing new applications of measurement-based quantum systems, Graphix provides a comprehensive architecture to support your work.

Installation

Install Graphix and customize your local environment.

Installation
Getting started

Learn the basics of Graphix and run your first MBQC program.

Getting started
Tutorials

Dive into the core MBQC objects implemented in Graphix, and learn to run various computations with guided examples.

Tutorials
Research workflows

Discover examples of recent work in MBQC reproduced and extended by simulations in Graphix.

Research workflows

About

Graphix was started in 2022 by Shinichi Sunami (University of Oxford) and Masato Fukushima (University of Tokyo, Fixstars Amplify). Daichi Sasaki, Yuki Watanabe and Sora Shiratani (University of Tokyo, Fixstars Amplify) later joined the team.

In 2023, the QAT team joined the efforts. Currently, Graphix is actively developped an maintained by Thierry Martinez, Mateo Uldemolins, Pranav Nair and Maxime Garnier (Inria).

The project has been supported by Fixstars Amplify and the Unitary Foundation, and currently participates in the French Hybrid Quantum Initiative.

How to cite us

If you use Graphix in your research, please consider citing the latest paper and the accompanying software release.

Papers

[1] M. Uldemolins, P. Nair, E. Graham, S. Sunami, T. Martinez, and M. Garnier, Graphix: A software framework for Measurement-Based Quantum Computation, arXiv:2608.24781 (2026).

@article{uldemolins2026_graphix,
   title={Graphix: A software framework for Measurement-Based Quantum Computation},
   author={Uldemolins, Mateo and Nair, Pranav and Graham, Emlyn and Sunami, Shinichi and Martinez, Thierry and Garnier, Maxime},
   journal={arXiv preprint arXiv:2608.24781},
   year={2026}
}

[2] S. Sunami, M. Fukushima. Graphix: optimizing and simulating measurement-based quantum computation on local-Clifford decorated graph, arxiv:2212.11975 (2022).

@article{sunami2022_graphix,
   title={Graphix: Optimizing and simulating measurement-based quantum computation on local-Clifford decorated graph},
   author={Sunami, Shinichi and Fukushima, Masato},
   journal={arXiv preprint arXiv:2212.11975},
   year={2022}
}

Software

M. Uldemolins, M. Fukushima, E. Graham, P. Nair, D. Sasaki, S. Shiratani, Y. Watanabe, T. Martinez, M. Garnier, and S. Sunami, “Graphix” (v0.4), Zenodo (2026), https://doi.org/10.5281/zenodo.21997813

@software{graphix_v04,
   author    = {Uldemolins, Mateo and Fukushima, Masato and
               Graham, Emlyn and Nair, Pranav and Sasaki, Daichi and
               Shiratani, Sora and Watanabe, Yuki and
               Martinez, Thierry and Garnier, Maxime and Sunami, Shinichi},
   title     = {Graphix},
   version   = {0.4},
   year      = {2026},
   publisher = {Zenodo},
   doi       = {10.5281/zenodo.21997813},
}
GitHub API reference Plugins