Quantum-Enhanced Optimization via Hierarchical State Space Representation

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum-enhanced optimization aims to accelerate the solution of complex optimization problems by utilizing quantum phenomena. This paper proposes a novel framework, Quantum-Enhanced Optimization via Hierarchical State Space Representation, where the problem space is organized hierarchically, leveraging quantum algorithms to facilitate efficient exploration of high-dimensional landscapes. This approach addresses limitations of traditional optimization methods, particularly when faced with intricate and complex problem settings. We detail the design of a hierarchical state space representation and the implementation of quantum algorithms to improve the search process. The core claim is that this framework will significantly enhance the performance of optimization tasks, offering improved efficiency and scalability compared to conventional methods. This research explores the potential of quantum mechanics to represent and navigate complex problem spaces, leading to a more effective solution process.

DOI: 10.5281/zenodo.22635458

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