Dynamic scaling, data-collapse and self-similarity in Barabási-Albert networks

Details Dynamic scaling, data-collapse and self-similarity in Barabási-Albert networks Dynamic scaling, data-collapse and self-similarity in Barabási-Albert networks

2011-01-25

arxiv.org/abs/1101.4730v2

J. Phys. A: Math. Theor. 44, 175101 (2011)

Physics

Condensed Matter

Statistical Mechanics

5 pages, six figures, Minor changes in the title, abstract, figures and in the text in response to referee reports

Scientific paper

10.1088/1751-8113/44/17/175101

In this article, we show that if each node of the Barab\'{a}si-Albert (BA) network is characterized by the generalized degree $q$, i.e. the product of their degree $k$ and the square root of their respective birth time, then the distribution function $F(q,t)$ exhibits dynamic scaling $F(q,t\rightarrow \infty)\sim t^{-1/2}\phi(q/t^{1/2})$ where $\phi(x)$ is the scaling function. We verified it by showing that a series of distinct $F(q,t)$ vs $q$ curves for different network sizes $N$ collapse onto a single universal curve if we plot $t^{1/2}F(q,t)$ vs $q/t^{1/2}$ instead. Finally, we show that the BA network falls into two universality classes depending on whether new nodes arrive with single edge ($m=1$) or with multiple edges ($m>1$).

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