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arXiv 0801.1395cond-mat.dis-nn
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无序递归网络的标度

Scaling of disordered recursive networks

Liang Tian, Da-Ning Shi

摘要:

在这个简短的报告中,我们提出了一个递归网络的无序版本。根据结构参数$u$和$v$,网络是具有有限分形维数$d_{f}$的分形或具有无限分形维数的超限分形(transfractal)。分析和模拟研究了度和维数的标度行为,发现其与有序递归网络的标度行为不同。transfractal维数$\tilde{d}_f$最近被引入来区分具有无穷分形维数的网络之间的差异,对于transfractal网络,其标度为$\tilde{d}_f\sim \frac{1}{u+v-1}$。有趣的是,发现含$u=v$的分形网络的分形维数在$u$的大极限下接近3,这被认为是无序的影响。我们还研究了这类网络上的扩散过程,数值上观察到扩散时间的标度行为,分形网络为$τ\sim N^{(d_{f}+1)/d_{f}}$,transfractal网络为$τ\sim \frac{1}{\tilde{d}_f}N$.我们认为,后一种关系将使我们对transfractal维数有进一步的理解。

英文摘要:

In this brief report, we present a disordered version of recursive networks. Depending on the structural parameters $u$ and $v$, the networks are either fractals with a finite fractal dimension $d_{f}$ or transfinite fractals (transfractal) with a infinite fractal dimension. The scaling behavior of degree and dimensionality are studied analytically and by simulations, which are found to be different from those in ordered recursive networks. The transfractal dimension $\tilde{d}_f$, which is recently introduced to distinguish the differences between networks with infinite fractal dimension, scales as $\tilde{d}_f\sim \frac{1}{u+v-1}$ for transfractal networks. Interestingly, the fractal dimension for fractal networks with $u=v$ is found to approach 3 in large limit of $u$, which is thought to be the effect of disorder. We also investigate the diffusion process on this family of networks, and the scaling behavior of diffusion time is observed numercally as $τ\sim N^{(d_{f}+1)/d_{f}}$ for fractal networks and $τ\sim \frac{1}{\tilde{d}_f}N$ for transfractal ons. We think that the later relation will give a further understanding of transfractal dimension.

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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