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随机临界点处局部序参量的多重分形统计:在具有无序性的浸润转变中的应用。

Multifractal statistics of the local order parameter at random critical points: application to wetting transitions with disorder.

作者信息

Monthus Cécile, Garel Thomas

机构信息

Service de Physique Théorique, CEA/DSM/SPhT, Unité de recherche associée au CNRS, 91191 Gif-sur-Yvette cedex, France.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Aug;76(2 Pt 1):021114. doi: 10.1103/PhysRevE.76.021114. Epub 2007 Aug 21.

Abstract

Disordered systems present multifractal properties at criticality. In particular, as discovered by Ludwig [A.W.W. Ludwig, Nucl. Phys. B 330, 639 (1990)] in the case of a diluted two-dimensional Potts model, the moments rho(q) (r) of the local order parameter rho(r) scale with a set x(q) of nontrivial exponents x(q) not = qx(1). We reexamine these ideas to incorporate more recent findings: (i) whenever a multifractal measure w(r) normalized over space sum(r) w(r) = 1 occurs in a random system, it is crucial to distinguish between the typical values and the disorder-averaged values of the generalized moments Y(q) = sum(r) w(q) (r), since they may scale with different generalized dimensions D(q) and D(q), and (ii), as discovered by Wiseman and Domany [S. Wiseman and E. Domany, Phys. Rev. E 52, 3469 (1995)], the presence of an infinite correlation length induces a lack of self-averaging at critical points for thermodynamic observables, in particular for the order parameter. After this general discussion, valid for any random critical point, we apply these ideas to random polymer models that can be studied numerically for large sizes and good statistics over the samples. We study the bidimensional wetting or the Poland-Scheraga DNA model with loop exponents c = 1.5 (marginal disorder) and c = 1.75 (relevant disorder). Finally, we argue that the presence of finite Griffiths-ordered clusters at criticality determines the asymptotic value x(q-->infinity) = d and the minimal value alpha(min) = D(q-->infinity) = d - x(1) of the typical multifractal spectrum f(alpha).

摘要

无序系统在临界点呈现多重分形特性。特别是,正如路德维希 [A.W.W. 路德维希,《核物理B》330,639 (1990)] 在稀释二维Potts模型的情形中所发现的,局部序参量ρ(r)的矩ρ(q)(r) 以一组非平凡指数x(q)(x(q)≠qx(1))进行标度。我们重新审视这些观点以纳入更新的发现:(i) 每当在一个随机系统中出现空间归一化的多重分形测度w(r)(∑r w(r)=1)时,区分广义矩Y(q)=∑r w(q)(r)的典型值和无序平均的值至关重要,因为它们可能以不同的广义维数D(q)和D(q)进行标度,以及 (ii) 正如怀斯曼和多马尼 [S. 怀斯曼和E. 多马尼,《物理评论E》52,3469 (1995)] 所发现的,无限关联长度的存在导致热力学可观测量在临界点缺乏自平均性,特别是对于序参量。在这个对任何随机临界点都有效的一般性讨论之后,我们将这些观点应用于随机聚合物模型,对于大尺寸和样本上良好的统计量,这些模型可以进行数值研究。我们研究具有环指数c = 1.5(边缘无序)和c = 1.75(相关无序)的二维浸润或波兰 - 谢拉加DNA模型。最后,我们认为在临界点有限格里菲斯有序簇的存在决定了典型多重分形谱f(α)的渐近值x(q→∞)=d和最小值α(min)=D(q→∞)=d - x(1)。

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