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摘要翻译：
复杂网络的结构和动力学通常涉及度分布、聚类、最短路径长度和其他图的性质。尽管这些概念已经被分析用于抽象空间上的图，但许多网络碰巧嵌入到度量排列中，在度量排列中顶点之间的地理距离起着至关重要的作用。本文提出了一种考虑节点间地理距离的生长网络模型：节点位置越近，连接概率越大。在此框架下，分析了随机选择的顶点的平均度、度分布和最短路径长度。
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英文标题：
《Solvable Metric Growing Networks》
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作者：
M. O. Hase and J. F. F. Mendes
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最新提交年份：
2008
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分类信息：
一级分类：Physics 物理学
二级分类：Statistical Mechanics 统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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英文摘要：
Structure and dynamics of complex networks usually deal with degree distributions, clustering, shortest path lengths and other graph properties. Although these concepts have been analysed for graphs on abstract spaces, many networks happen to be embedded in a metric arrangement, where the geographic distance between vertices plays a crucial role. The present work proposes a model for growing network that takes into account the geographic distance between vertices: the probability that they are connected is higher if they are located nearer than farther. In this framework, the mean degree of vertices, degree distribution and shortest path length between two randomly chosen vertices are analysed.
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PDF链接：
https://arxiv.org/pdf/711.2999
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