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具有记忆的可解随机游走模型及其与反常扩散马尔可夫模型的关系。

Solvable random-walk model with memory and its relations with Markovian models of anomalous diffusion.

作者信息

Boyer D, Romo-Cruz J C R

机构信息

Instituto de Física, Universidad Nacional Autónoma de México, D.F. 04510, México and Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, D.F. 04510, México.

Instituto de Física, Universidad Nacional Autónoma de México, D.F. 04510, México.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Oct;90(4):042136. doi: 10.1103/PhysRevE.90.042136. Epub 2014 Oct 22.

Abstract

Motivated by studies on the recurrent properties of animal and human mobility, we introduce a path-dependent random-walk model with long-range memory for which not only the mean-square displacement (MSD) but also the propagator can be obtained exactly in the asymptotic limit. The model consists of a random walker on a lattice, which, at a constant rate, stochastically relocates at a site occupied at some earlier time. This time in the past is chosen randomly according to a memory kernel, whose temporal decay can be varied via an exponent parameter. In the weakly non-Markovian regime, memory reduces the diffusion coefficient from the bare value. When the mean backward jump in time diverges, the diffusion coefficient vanishes and a transition to an anomalous subdiffusive regime occurs. Paradoxically, at the transition, the process is an anticorrelated Lévy flight. Although in the subdiffusive regime the model exhibits some features of the continuous time random walk with infinite mean waiting time, it belongs to another universality class. If memory is very long-ranged, a second transition takes place to a regime characterized by a logarithmic growth of the MSD with time. In this case the process is asymptotically Gaussian and effectively described as a scaled Brownian motion with a diffusion coefficient decaying as 1/t.

摘要

受关于动物和人类移动性的循环特性研究的启发,我们引入了一个具有长程记忆的路径依赖随机游走模型,对于该模型,不仅均方位移(MSD),而且传播子在渐近极限下都可以精确获得。该模型由晶格上的随机游走者组成,它以恒定速率随机重新定位到某个较早时间占据的位置。过去的这个时间根据记忆核随机选择,其时间衰减可以通过一个指数参数来改变。在弱非马尔可夫 regime 中,记忆会使扩散系数从裸值减小。当平均时间向后跳跃发散时,扩散系数消失,并且会发生向反常亚扩散 regime 的转变。矛盾的是,在转变处,该过程是反相关的 Lévy 飞行。尽管在亚扩散 regime 中该模型表现出具有无限平均等待时间的连续时间随机游走的一些特征,但它属于另一个普适类。如果记忆是非常长程的,会发生第二次转变,进入一个以 MSD 随时间对数增长为特征的 regime。在这种情况下,该过程渐近高斯分布,并有效地描述为扩散系数随 1/t 衰减的缩放布朗运动。

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