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arXiv 1306.2917math.PR
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图上路的标度性质

Scaling Properties of Paths on Graphs

R. Edwards, E. Foxall, T. J. Perkins

摘要:

设$G$是一个顶点数和边数都很大的有向图,并给$G$上的每条边赋予一个正的权.固定顶点$u$和$v$,并考虑从$u$开始到$v$结束的路径集合,在沿途的任意位置处自相交。对于每条路径,对其边的权重求和,然后按递增顺序列出路径权重。这个序列的渐近行为的描述,在结构和类型的强连接组件的图形。作为特殊情况,对于马尔可夫链,路径的渐进概率服从幂律缩放或较弱类型的缩放,具体取决于转移阵的结构。这推广了Mandelbrot和其他人以前的工作,他们建立了特殊类别的马尔可夫链的渐近幂律标度。

英文摘要:

Let $G$ be a directed graph on finitely many vertices and edges, and assign a positive weight to each edge on $G$. Fix vertices $u$ and $v$ and consider the set of paths that start at $u$ and end at $v$, self-intersecting in any number of places along the way. For each path, sum the weights of its edges, and then list the path weights in increasing order. The asymptotic behaviour of this sequence is described, in terms of the structure and type of strongly connected components on the graph. As a special case, for a Markov chain the asymptotic probability of paths obeys either a power law scaling or a weaker type of scaling, depending on the structure of the transition matrix. This generalizes previous work by Mandelbrot and others, who established asymptotic power law scaling for special classes of Markov chains.

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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