QAOAKit: A Toolkit for Reproducible Study, Application, and Verification of the QAOA

Understand

Understanding the best known parameters, performance, and systematic behavior of the Quantum Approximate Optimization Algorithm (QAOA) remain open research questions, even as the algorithm gains popularity.

• We introduce QAOAKit, a Python toolkit for the QAOA built for exploratory research.
• QAOAKit is a unified repository of preoptimized QAOA parameters and circuit generators for common quantum simulation frameworks.
• We combine, standardize, and cross-validate previously known parameters for the MaxCut problem, and incorporate this into QAOAKit.