分层格上各向同性定向渗流的临界指数。

IF 2.4 3区 物理与天体物理 Q2 PHYSICS, FLUIDS & PLASMAS
Samuel Dos S Costa, Aurelio W T de Noronha, André P Vieira, José S Andrade, André A Moreira
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引用次数: 0

摘要

我们使用重整化群和蒙特卡罗计算来研究分层格上的各向同性定向渗透。我们描述了一种一般的重整化群方法来精确地确定这些格的临界指数。这种方法虽然比聚类生成函数的方法简单,但与之等效,并且可以应用于各种层次格。对于各向同性定向渗流,我们需要确定两个临界指数,即β_{scc}和β_{out},它们分别与渗流阈值附近的巨大强连通分量和巨大out分量相关。我们的方法适用于不同结构的层次晶格,特别是小世界层次晶格,其中包括远程键,并表现出一种爆炸渗透形式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Critical exponents for isotropically directed percolation on hierarchical lattices.

We use renormalization-group and Monte Carlo calculations to investigate isotropically directed percolation on hierarchical lattices. We describe a general renormalization-group approach to exactly determine the critical exponents for these lattices. This approach is equivalent to, albeit simpler than, the method of cluster generating functions and can be applied to various hierarchical lattices. In the case of isotropically directed percolation, we need to determine two critical exponents, namely, β_{scc} and β_{out} associated, respectively, with the giant strongly connected component and the giant out component in the neighborhood of the percolation threshold. Our method is applied to different constructions of the hierarchical lattice, in particular, to a small-world hierarchical lattice which includes long-range bonds and exhibits a form of explosive percolation.

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来源期刊
Physical Review E
Physical Review E PHYSICS, FLUIDS & PLASMASPHYSICS, MATHEMAT-PHYSICS, MATHEMATICAL
CiteScore
4.50
自引率
16.70%
发文量
2110
期刊介绍: Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.
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