基于自适应的量子计算的拓扑优化

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum computing, leveraging the bizarre properties of quantum mechanics, holds immense potential for revolutionizing various fields. However, achieving practical quantum computation necessitates overcoming fundamental challenges, particularly in algorithm design and optimization. This paper explores the application of a novel self-adaptive quantum optimization algorithm, inspired by the principles of quantum topology and entanglement. We introduce a system that dynamically adjusts quantum parameters to enhance computational efficiency and explore novel solutions to complex problems. The core mechanism centers around leveraging quantum entanglement to guide the optimization process, ultimately leading to improved performance. The proposed algorithm offers a promising approach to addressing the limitations of current quantum computing techniques and opens new avenues for scientific discovery and technological advancement.

DOI: 10.5281/zenodo.22297561

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