基于自适应的量子计算的非线性优化算法

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper presents a novel quantum optimization algorithm based on adaptive quantum computation, leveraging quantum entanglement and quantum simulation to efficiently solve non-linear optimization problems. Traditional optimization methods often suffer from computational limitations, necessitating substantial resources. This research introduces a dynamically adjusted quantum algorithm that exploits quantum entanglement and quantum simulation to achieve significantly improved performance compared to existing techniques. The core mechanism centers on a carefully designed quantum circuit architecture that utilizes entanglement to explore the solution space more effectively and efficiently. This paper details the algorithm's design, analysis of its performance, and potential applications across diverse non-linear optimization scenarios.

DOI: 10.5281/zenodo.22581842

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