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arXiv 1102.5680math.PRmath.CO
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超小随机网络中的典型距离

Typical distances in ultrasmall random networks

Steffen Dereich, Christian Mönch, Peter Mörters

摘要:

我们证明了在具有幂律指数$τ\in(2,3)$的偏好连接模型中,巨分支中随机选择的顶点之间的距离渐近等于$(4+o(1))\, \frac{\log\log N}{-\log (τ-2)}$,其中$N$表示节点数.这是具有相同幂律指数的几种类型的配置模型获得的值的两倍。额外因子揭示了偏好连接图中典型最短路的不同结构。

英文摘要:

We show that in preferential attachment models with power-law exponent $τ\in(2,3)$ the distance between randomly chosen vertices in the giant component is asymptotically equal to $(4+o(1))\, \frac{\log\log N}{-\log (τ-2)}$, where $N$ denotes the number of nodes. This is twice the value obtained for several types of configuration models with the same power-law exponent. The extra factor reveals the different structure of typical shortest paths in preferential attachment graphs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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