Quantum Accelerated Simulated Annealing

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Simulated annealing (SA) is a widely used metaheuristic algorithm for solving optimization problems. However, its performance is often limited by the slow exploration of the search space. This paper explores the potential of accelerating simulated annealing using quantum computing. We propose a framework where the search space of SA is mapped to the quantum state space, leveraging quantum superposition and interference to expedite the search for the global optimum. The core claim is that quantum computation can significantly speed up the search process within simulated annealing. The mechanism relies on utilizing quantum algorithms to explore the solution space far more efficiently than classical methods. This work introduces a novel approach to optimization, demonstrating the potential of harnessing quantum mechanical phenomena to enhance the performance of classical optimization algorithms. The theoretical framework and conceptual design are presented, outlining a possible architecture for a quantum-accelerated simulated annealing system. The potential speedup is analyzed, and future research directions are discussed.

DOI: 10.5281/zenodo.22635288

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