We introduce OpenQAOA, a Python open-source multi-backend Software Development Kit to create, customise, and execute the Quantum Approximate Optimisation Algorithm (QAOA) on Noisy Intermediate-Scale Quantum (NISQ) devices and simulators. OpenQAOA facilitates the creation of QAOA workflows, removing the more tedious and repetitive aspects of implementing variational quantum algorithms. It standardises and automates tasks such as circuit creation across different backends, ansatz parametrisation, the optimisation loop, the formatting of results, and extensions of QAOA such as Recursive QAOA. OpenQAOA is designed to simplify and enhance research on QAOA, providing a robust and consistent framework for experimentation with, and deployment of, the algorithm and its variations. Importantly, a heavy emphasis is placed on the provision of tools to enable QAOA computations at the scale of hundreds or thousands of qubits.
@article{arxiv.2210.08695,
title = {OpenQAOA -- An SDK for QAOA},
author = {Vishal Sharma and Nur Shahidee Bin Saharan and Shao-Hen Chiew and Ezequiel Ignacio Rodríguez Chiacchio and Leonardo Disilvestro and Tommaso Federico Demarie and Ewan Munro},
journal= {arXiv preprint arXiv:2210.08695},
year = {2022}
}