A Method Inspired by One-Dimensional Discrete-Time Quantum Walks for Influential Node Identification.

IF 2.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Entropy Pub Date : 2025-06-14 DOI:10.3390/e27060634
Wen Liang, Yifan Wang, Qiwei Liu, Wenbo Zhang
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引用次数: 0

Abstract

Identifying influential nodes in complex networks is essential for a wide range of applications, from social network analysis to enhancing infrastructure resilience. While quantum walk-based methods offer potential advantages, existing approaches face challenges in dimensionality, computational efficiency, and accuracy. To address these limitations, this study proposes a novel method inspired by the one-dimensional discrete-time quantum walk (IOQW). This design enables the development of a simplified shift operator that leverages both self-loops and the network's structural connectivity. Furthermore, degree centrality and path-based features are integrated into the coin operator, enhancing the accuracy and scalability of the IOQW framework. Comparative evaluations against state-of-the-art quantum and classical methods demonstrate that IOQW excels in capturing both local and global topological properties while maintaining a low computational complexity of O(N⟨k⟩), where ⟨k⟩ denotes the average degree. These advancements establish IOQW as a powerful and practical tool for influential node identification in complex networks, bridging quantum-inspired techniques with real-world network science applications.

基于一维离散时间量子行走的影响节点识别方法。
识别复杂网络中的有影响的节点对于从社会网络分析到增强基础设施弹性的广泛应用至关重要。虽然基于量子行走的方法提供了潜在的优势,但现有的方法在维度、计算效率和准确性方面面临挑战。为了解决这些限制,本研究提出了一种受一维离散时间量子行走(IOQW)启发的新方法。这种设计使简化移位算子的开发成为可能,它既利用了自环路,又利用了网络的结构连通性。此外,将度中心性和基于路径的特征集成到硬币算子中,提高了IOQW框架的准确性和可扩展性。对最先进的量子和经典方法的比较评估表明,IOQW在捕获局部和全局拓扑特性方面表现出色,同时保持O(N⟨k⟩)的低计算复杂性,其中⟨k⟩表示平均程度。这些进步使IOQW成为复杂网络中有影响力的节点识别的强大实用工具,将量子启发技术与现实世界的网络科学应用连接起来。
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来源期刊
Entropy
Entropy PHYSICS, MULTIDISCIPLINARY-
CiteScore
4.90
自引率
11.10%
发文量
1580
审稿时长
21.05 days
期刊介绍: Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.
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