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arXiv 0804.1768cond-mat.stat-mechcond-mat.dis-nnphysics.soc-ph
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生长中复杂网络的凝聚动力学

Dynamics of condensation in growing complex networks

Luca Ferretti, Ginestra Bianconi

摘要:

一个冷凝过渡预测不断增长的技术网络的优先连接和竞争质量的节点,如所描述的健身模型。当这种凝聚发生时,节点获得网络所有链路的有限部分。早期的研究基于稳态度分布和对玻色-爱因斯坦凝聚的映射,能够确定临界点。在这里,我们描述了冷凝的动力学,我们提出的证据表明,在冷凝温度以下,动力学会减慢,并且单个节点(不一定是网络中的最佳节点)会在很长一段时间内成为赢家。当新链路确定性地连接到网络的最高质量节点时,出现这种现象的特征时间t* 在临界点和$T -> 0$都发散。

英文摘要:

A condensation transition was predicted for growing technological networks evolving by preferential attachment and competing quality of their nodes, as described by the fitness model. When this condensation occurs a node acquires a finite fraction of all the links of the network. Earlier studies based on steady state degree distribution and on the mapping to Bose-Einstein condensation, were able to identify the critical point. Here we characterize the dynamics of condensation and we present evidence that below the condensation temperature there is a slow down of the dynamics and that a single node (not necessarily the best node in the network) emerges as the winner for very long times. The characteristic time t* at which this phenomenon occurs diverges both at the critical point and at $T -> 0$ when new links are attached deterministically to the highest quality node of the network.

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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