基于量子自适应的图论算法

Jincheng Zhang

Published Aug 29, 2026• 0 citations

Abstract

This paper introduces a novel graph theory algorithm, termed "Quantum Adaptive Graph Topology" (QAGT), leveraging the principles of quantum self-adaptation. Traditional graph theory algorithms often operate on static, fixed graph structures, limiting their ability to fully exploit the dynamic nature of quantum states. QAGT employs a quantum-based adaptation mechanism that automatically adjusts graph topology, leading to improved performance in various graph applications. This research explores the potential of utilizing quantum phenomena to enhance graph analysis and representation. We present a detailed theoretical analysis of the algorithm's core mechanisms and demonstrate its effectiveness through illustrative examples. The study underscores the transformative role of quantum self-adaptation in graph theory, paving the way for more sophisticated and efficient graph representations.

DOI: 10.5281/zenodo.22154342

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