Servedio Vito D P, Caldarelli Guido, Buttà Paolo
INFM UdR Roma1 and Dipartimento di Fisica, Università La Sapienza, Piazzale A. Moro 2, I-00185 Roma, Italy.
Phys Rev E Stat Nonlin Soft Matter Phys. 2004 Nov;70(5 Pt 2):056126. doi: 10.1103/PhysRevE.70.056126. Epub 2004 Nov 23.
We study a recent model of random networks based on the presence of an intrinsic character of the vertices called fitness. The vertex fitnesses are drawn from a given probability distribution density. The edges between pairs of vertices are drawn according to a linking probability function depending on the fitnesses of the two vertices involved. We study here different choices for the probability distribution densities and the linking functions. We find that, irrespective of the particular choices, the generation of scale-free networks is straightforward. We then derive the general conditions under which scale-free behavior appears. This model could then represent a possible explanation for the ubiquity and robustness of such structures.
我们研究了一种基于顶点内在特征(称为适应性)的随机网络的最新模型。顶点适应性是从给定的概率分布密度中抽取的。顶点对之间的边是根据一个依赖于所涉及的两个顶点适应性的连接概率函数绘制的。我们在这里研究概率分布密度和连接函数的不同选择。我们发现,无论具体选择如何,无标度网络的生成都是直接的。然后我们推导出出现无标度行为的一般条件。该模型可以为这类结构的普遍性和稳健性提供一种可能的解释。