基于自组织网络的量子算法优化

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computing is poised to revolutionize numerous fields, offering unparalleled computational power. However, scaling up quantum computers faces significant challenges, particularly concerning algorithm efficiency. This paper explores the application of a novel quantum algorithm optimization framework based on self-organizing networks. We propose a dynamic allocation strategy leveraging these networks to optimize quantum algorithms, aiming to enhance their performance and scalability. The core mechanism focuses on structuring the quantum system using self-organizing networks, enabling efficient resource allocation and reducing computational complexity. This work presents a framework demonstrating significant improvements in quantum algorithm execution speed compared to existing optimization techniques. The potential impact of this approach is substantial, paving the way for practical quantum computation. This research contributes to the advancement of quantum algorithm design and provides a foundation for exploring the full potential of self-organizing networks in quantum computing.

DOI: 10.5281/zenodo.22192746

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