Anomalous random networks

Fuente: arXiv
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Auteurs principaux: Zhang, Hong, Li, Guohua
Format: Preprint
Publié: 2024
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author Zhang, Hong
Li, Guohua
author_facet Zhang, Hong
Li, Guohua
contents After the groundbreaking work of Erd$\ddot{o}$s-R$\acute{e}$nyi random graph, the random networks has made great progress in recent years. One of the eye-catching modeling is time-varying random network model capable of encoding the instantaneous time description of the network dynamics. To further describe the random duration time for the nodes to be inactive, we herein propose a dinner party anomalous random networks model, and derive the analytical solution of the probability density function for the node being active at a given time. Moreover, we investigate the gift delivery and viral transmission in dinner party random networks. This work provides new quantitative insights in describing random networks, and could help model other uncertainty phenomena in real networks.
format Preprint
id arxiv_https___arxiv_org_abs_2406_18882
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Anomalous random networks
Zhang, Hong
Li, Guohua
Disordered Systems and Neural Networks
After the groundbreaking work of Erd$\ddot{o}$s-R$\acute{e}$nyi random graph, the random networks has made great progress in recent years. One of the eye-catching modeling is time-varying random network model capable of encoding the instantaneous time description of the network dynamics. To further describe the random duration time for the nodes to be inactive, we herein propose a dinner party anomalous random networks model, and derive the analytical solution of the probability density function for the node being active at a given time. Moreover, we investigate the gift delivery and viral transmission in dinner party random networks. This work provides new quantitative insights in describing random networks, and could help model other uncertainty phenomena in real networks.
title Anomalous random networks
topic Disordered Systems and Neural Networks
url https://arxiv.org/abs/2406.18882