Quantum Adaptive Optimization Algorithm (QOA)

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum Adaptive Optimization Algorithm (QOA) presents a novel approach to optimization utilizing quantum entanglement to accelerate the search process. This paper details the design and implementation of QOA, highlighting its core mechanism – leveraging quantum entanglement to facilitate rapid convergence and enhanced optimization strategies. The research focuses on establishing a robust framework that can effectively address complex problems traditionally challenging traditional optimization techniques. This work introduces a new algorithmic approach with the potential to significantly improve the efficiency and effectiveness of optimization across a range of applications. The core claim emphasizes the utilization of quantum entanglement for rapid solution discovery and improved optimization strategies.

DOI: 10.5281/zenodo.22253471

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