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Graphix: A software framework for Measurement-Based Quantum Computation

arXiv
Authors: Mateo Uldemolins, Pranav Nair, Emlyn Graham, Shinichi Sunami, Thierry Martinez, Maxime Garnier

Year

2026

Paper ID

76377

Status

Preprint

Abstract Read

~2 min

Abstract Words

122

Citations

N/A

Abstract

Measurement-based quantum computing (MBQC) is a powerful model for quantum computation, but dedicated software tools that bridge its theoretical foundations with practical research workflows remain limited. We present Graphix, a software framework for MBQC written in Python that provides a unified environment for developing, integrating, and exploring measurement-based protocols and algorithms. Graphix establishes a modular, extensible, and user-friendly architecture for the compilation and simulation of quantum computations in the MBQC model with abstractions closely aligned with the theoretical formulations of MBQC. Through examples drawn from recent research on MBQC, we demonstrate Graphix's ability to reproduce and extend previous results. Graphix thus provides a software infrastructure for MBQC, supporting education and research while enabling collaborative development and accelerating the transition toward practical implementations.

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  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
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  • Measurement-based quantum computing (MBQC) is a powerful model for quantum computation, but dedicated software tools that bridge its theoretical foundations with practical...

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