基于自适应量子计算的拓扑优化算法

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper introduces a novel quantum optimization algorithm, termed "Adaptive Topological Optimization," designed to enhance the performance of quantum computations. Traditional optimization methods often struggle with the inherent complexity of quantum systems, necessitating a shift towards quantum-specific approaches. This research focuses on leveraging the unique properties of quantum mechanics – particularly the topological nature of quantum states – to guide optimization processes, offering a potential paradigm shift in quantum algorithm design. The core of this algorithm utilizes a dynamically adjusted quantum state to explore the solution space more efficiently and identify optimal solutions with superior performance. We demonstrate the effectiveness of this approach through a series of simulations and preliminary results, highlighting its potential to significantly improve the efficiency and scalability of quantum computations. The paper concludes with a discussion of the algorithm's underlying principles, its potential applications, and future research directions.

DOI: 10.5281/zenodo.22242035

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