{"title":"阐明每个节点都有自己寿命的网络的特点","authors":"Nobutoshi Ikeda","doi":"10.1016/j.physa.2024.130149","DOIUrl":null,"url":null,"abstract":"<div><div>Growth is regarded as an important mechanism for explaining the structures of real networks. However, when the increase in the number of nodes is suppressed owing to their lifetime, the growth property alone is not sufficient to explain even fundamental network properties, such as the scale-free property. In this paper, we propose a network model that considers the lifetime of nodes and the excess addition of local internal links as a mechanism that supports network structures. By investigating the model network, we aimed to elucidate the network characteristics supported by local interactions between nodes via their common neighbors even when the rates of node addition and deletion were balanced. We found that the stationary state of the number of nodes is characterized by a scale-free property with the power-law exponent <span><math><mrow><mi>γ</mi><mo>≃</mo><mn>1</mn></mrow></math></span> and localization of the peaks at <span><math><mrow><mi>l</mi><mo>=</mo><mn>2</mn></mrow></math></span> in the distance distributions of neighboring nodes (DDN) as the node degree <span><math><mi>k</mi></math></span> increases. The specific behavior of the DDN explains the very slow decrease in the clustering strength <span><math><mrow><mi>C</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></math></span> with <span><math><mi>k</mi></math></span> compared with the normal behavior <span><math><mrow><mi>C</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>∼</mo><msup><mrow><mi>k</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span> and the accelerated growth of the neighborhood graph of each node. Moreover, we showed that some real networks share local structures similar to those of the model network. These findings suggest that the same mechanism as that of the proposed model plays an essential role in supporting the local structures of some real networks.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"654 ","pages":"Article 130149"},"PeriodicalIF":2.8000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Elucidation of characteristics of networks where every node has its own lifetime\",\"authors\":\"Nobutoshi Ikeda\",\"doi\":\"10.1016/j.physa.2024.130149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Growth is regarded as an important mechanism for explaining the structures of real networks. However, when the increase in the number of nodes is suppressed owing to their lifetime, the growth property alone is not sufficient to explain even fundamental network properties, such as the scale-free property. In this paper, we propose a network model that considers the lifetime of nodes and the excess addition of local internal links as a mechanism that supports network structures. By investigating the model network, we aimed to elucidate the network characteristics supported by local interactions between nodes via their common neighbors even when the rates of node addition and deletion were balanced. We found that the stationary state of the number of nodes is characterized by a scale-free property with the power-law exponent <span><math><mrow><mi>γ</mi><mo>≃</mo><mn>1</mn></mrow></math></span> and localization of the peaks at <span><math><mrow><mi>l</mi><mo>=</mo><mn>2</mn></mrow></math></span> in the distance distributions of neighboring nodes (DDN) as the node degree <span><math><mi>k</mi></math></span> increases. The specific behavior of the DDN explains the very slow decrease in the clustering strength <span><math><mrow><mi>C</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow></mrow></math></span> with <span><math><mi>k</mi></math></span> compared with the normal behavior <span><math><mrow><mi>C</mi><mrow><mo>(</mo><mi>k</mi><mo>)</mo></mrow><mo>∼</mo><msup><mrow><mi>k</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></mrow></math></span> and the accelerated growth of the neighborhood graph of each node. Moreover, we showed that some real networks share local structures similar to those of the model network. These findings suggest that the same mechanism as that of the proposed model plays an essential role in supporting the local structures of some real networks.</div></div>\",\"PeriodicalId\":20152,\"journal\":{\"name\":\"Physica A: Statistical Mechanics and its Applications\",\"volume\":\"654 \",\"pages\":\"Article 130149\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physica A: Statistical Mechanics and its Applications\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0378437124006587\",\"RegionNum\":3,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHYSICS, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physica A: Statistical Mechanics and its Applications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378437124006587","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
摘要
增长被认为是解释真实网络结构的重要机制。然而,当节点数量的增长因节点寿命而受到抑制时,仅靠增长特性甚至不足以解释基本的网络特性,如无标度特性。在本文中,我们提出了一种网络模型,将节点的生命周期和局部内部链接的过度增加作为支持网络结构的机制。通过对模型网络的研究,我们旨在阐明即使在节点增减率平衡的情况下,节点之间通过其共同邻居进行的局部互动所支持的网络特性。我们发现,随着节点度 k 的增加,节点数的静止状态具有无标度特性,即幂律指数 γ≃1,并且相邻节点距离分布(DDN)的峰值定位在 l=2 处。DDN 的特殊行为解释了聚类强度 C(k) 随 k 下降的速度与正常行为 C(k)∼k-1 相比非常缓慢,以及每个节点的邻域图加速增长的原因。此外,我们还发现一些真实网络的局部结构与模型网络相似。这些发现表明,与模型相同的机制在支持某些真实网络的局部结构方面发挥了重要作用。
Elucidation of characteristics of networks where every node has its own lifetime
Growth is regarded as an important mechanism for explaining the structures of real networks. However, when the increase in the number of nodes is suppressed owing to their lifetime, the growth property alone is not sufficient to explain even fundamental network properties, such as the scale-free property. In this paper, we propose a network model that considers the lifetime of nodes and the excess addition of local internal links as a mechanism that supports network structures. By investigating the model network, we aimed to elucidate the network characteristics supported by local interactions between nodes via their common neighbors even when the rates of node addition and deletion were balanced. We found that the stationary state of the number of nodes is characterized by a scale-free property with the power-law exponent and localization of the peaks at in the distance distributions of neighboring nodes (DDN) as the node degree increases. The specific behavior of the DDN explains the very slow decrease in the clustering strength with compared with the normal behavior and the accelerated growth of the neighborhood graph of each node. Moreover, we showed that some real networks share local structures similar to those of the model network. These findings suggest that the same mechanism as that of the proposed model plays an essential role in supporting the local structures of some real networks.
期刊介绍:
Physica A: Statistical Mechanics and its Applications
Recognized by the European Physical Society
Physica A publishes research in the field of statistical mechanics and its applications.
Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents.
Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.