Suppr超能文献

波动随机图产生的复杂网络:隐藏变量分布的解析公式

Complex networks emerging from fluctuating random graphs: analytic formula for the hidden variable distribution.

作者信息

Abe Sumiyoshi, Thurner Stefan

机构信息

Institute of Physics, University of Tsukuba, Ibaraki 305-8571, Japan.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Sep;72(3 Pt 2):036102. doi: 10.1103/PhysRevE.72.036102. Epub 2005 Sep 2.

Abstract

In analogy to superstatistics, which connects Boltzmann-Gibbs statistical mechanics to its generalizations through temperature fluctuations, complex networks are constructed from fluctuating Erdös-Rényi random graphs. Using a quantum-mechanical method, the exact analytic formula for the hidden variable distribution is presented which describes the nature of the fluctuations and generates a generic degree distribution through the Poisson transformation. As an example, a static scale-free network is discussed and the corresponding hidden variable distribution is found to decay as a power law and to diverge at the origin.

摘要

类似于超统计(它通过温度涨落将玻尔兹曼 - 吉布斯统计力学与其推广形式联系起来),复杂网络由波动的厄多斯 - 雷尼随机图构建而成。使用量子力学方法,给出了隐藏变量分布的精确解析公式,该公式描述了涨落的性质,并通过泊松变换生成一般的度分布。作为一个例子,讨论了一个静态无标度网络,发现相应的隐藏变量分布按幂律衰减且在原点发散。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验