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arXiv 0804.1847cond-mat.dis-nn
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有限维无序系统的非平衡动力学:RG大时间流向“无限无序”不动点

Non-equilibrium dynamics of finite-dimensional disordered systems : RG flow towards an "infinite disorder" fixed point at large times

Cecile Monthus, Thomas Garel

摘要:

为了描述随机系统的非平衡动力学,我们最近引入了(C。Monthus和T. Garel,arxiv:0802.2502)一个可以定义为任何主方程的配置空间中的“强无序重整化”(RG)过程。在本文中,我们详细分析了大时间动力学的性质,每当RG流是对一些“无限无序”的不动点,其中的重正化障碍分布的宽度无限增长迭代。特别是,我们展示了如何强无序RG规则,然后可以简化,同时保持其渐近精确性,因为一个给定的重整化谷的首选出口通道通常占主导地位的渐近超过其他出口通道。我们解释了为什么本方法是一个明确的建设,有利于液滴缩放图片的动态是由对数增长的相干长度$l(t) \sim (\ln t)^{1/ψ}$,其中的统计障碍对应于一个非常强大的层次结构的山谷内谷。作为应用的一个例子,我们已经遵循数值RG流的情况下,在二维随机介质中的定向聚合物。完整的RG规则用于检查RG流是否朝向某个无限无序不动点,而简化的RG规则允许研究更大的尺寸并估计不动点的势垒指数$ψ$。

英文摘要:

To describe the non-equilibrium dynamics of random systems, we have recently introduced (C. Monthus and T. Garel, arxiv:0802.2502) a 'strong disorder renormalization' (RG) procedure in configuration space that can be defined for any master equation. In the present paper, we analyze in details the properties of the large time dynamics whenever the RG flow is towards some "infinite disorder" fixed point, where the width of the renormalized barriers distribution grows indefinitely upon iteration. In particular, we show how the strong disorder RG rules can be then simplified while keeping their asymptotic exactness, because the preferred exit channel out of a given renormalized valley typically dominates asymptotically over the other exit channels. We explain why the present approach is an explicit construction in favor of the droplet scaling picture where the dynamics is governed by the logarithmic growth of the coherence length $l(t) \sim (\ln t)^{1/ψ}$, and where the statistics of barriers corresponds to a very strong hierarchy of valleys within valleys. As an example of application, we have followed numerically the RG flow for the case of a directed polymer in a two-dimensional random medium. The full RG rules are used to check that the RG flow is towards some infinite disorder fixed point, whereas the simplified RG rules allow to study bigger sizes and to estimate the barrier exponent $ψ$ of the fixed point.

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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