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基于量子退火算法的复杂优化问题求解

Jincheng Zhang

Published Sep 6, 2026• 0 citations
Publisher

Abstract

This paper investigates the application of the Quantum Annealing (QA) algorithm to solve complex optimization problems. The core claim is that simulating a complex optimization problem's local search process through the QA's annealing process can effectively locate global optimal solutions. The mechanism involves mapping the solution space of an optimization problem onto the annealing path of QA, controlling the annealing rate and path to guide the solution towards the optimal point. This research leverages QA's inherent ability to mimic physical annealing, aiming to enhance optimization efficiency and accuracy. We present a framework for formulating and applying QA to various complex problems, highlighting its potential advantages over traditional optimization methods. This work contributes to the growing field of quantum computing by demonstrating a practical approach to tackling challenging optimization tasks. The results suggest that QA can be a viable alternative for achieving superior performance in specific optimization scenarios.

DOI
10.5281/zenodo.22445004

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