不可逆聚合与网络重整化
Irreversible Aggregation and Network Renormalization
摘要：
不可逆聚合是鉴于最近的工作重新规范化的复杂网络。它的标度律和相变与在后者中看到的逾渗转变有关。我们说明我们的观点，给出完整的解决方案的概率找到任何给定的状态在聚集过程$(k+1)X\to X$，给定一个固定数量的单位质量的粒子在初始状态。完全相同的概率分布和标度被发现在一维系统（一个平凡的网络）和良好的混合解决方案。这表明，在复杂网络的重正化中发现的标度律并不能证明它们是自相似的。
英文摘要：
Irreversible aggregation is revisited in view of recent work on renormalization of complex networks. Its scaling laws and phase transitions are related to percolation transitions seen in the latter. We illustrate our points by giving the complete solution for the probability to find any given state in an aggregation process $(k+1)X\to X$, given a fixed number of unit mass particles in the initial state. Exactly the same probability distributions and scaling are found in one dimensional systems (a trivial network) and well-mixed solutions. This reveals that scaling laws found in renormalization of complex networks do not prove that they are self-similar.
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