q Index Degree Distribution in Random Networks via Superstatistics
Abstract
In this study, we employ a superstatistical approach to construct q exponential and q Maxwell Boltzmann complex networks, generalizing the concept of scale free networks. By adjusting the crossover parameter {\lambda}, we control the degree of the q exponential plateau at low node degrees, allowing a smooth transition to pure power law degree distributions. Similarly, the parameter b modulates the q Maxwell Boltzmann curvature, facilitating a shift toward pure power law networks. This framework introduces a novel perspective for constructing and analyzing scale free networks. Our results show that these additional degrees of freedom significantly enhance the flexibility of both network types in terms of topological and transport properties, including clustering coefficients, small world characteristics, and resilience to attacks. Future research will focus on exploring the dynamic properties of these networks, offering promising directions for further investigation.
Keywords
Cite
@article{arxiv.2411.08066,
title = {q Index Degree Distribution in Random Networks via Superstatistics},
author = {Huilin Wang and Weibing Deng},
journal= {arXiv preprint arXiv:2411.08066},
year = {2024}
}