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从扩散到反常扩散:爱因斯坦布朗运动百年之后

From diffusion to anomalous diffusion: a century after Einstein's Brownian motion.

作者信息

Sokolov I M, Klafter J

机构信息

Institut für Physik, Humboldt-Universität zu Berlin, Newtonstrasse 15, D-12489 Berlin, Germany.

出版信息

Chaos. 2005 Jun;15(2):26103. doi: 10.1063/1.1860472.

Abstract

Einstein's explanation of Brownian motion provided one of the cornerstones which underlie the modern approaches to stochastic processes. His approach is based on a random walk picture and is valid for Markovian processes lacking long-term memory. The coarse-grained behavior of such processes is described by the diffusion equation. However, many natural processes do not possess the Markovian property and exhibit anomalous diffusion. We consider here the case of subdiffusive processes, which correspond to continuous-time random walks in which the waiting time for a step is given by a probability distribution with a diverging mean value. Such a process can be considered as a process subordinated to normal diffusion under operational time which depends on this pathological waiting-time distribution. We derive two different but equivalent forms of kinetic equations, which reduce to known fractional diffusion or Fokker-Planck equations for waiting-time distributions following a power law. For waiting time distributions which are not pure power laws one or the other form of the kinetic equation is advantageous, depending on whether the process slows down or accelerates in the course of time.

摘要

爱因斯坦对布朗运动的解释为现代随机过程方法奠定了基石之一。他的方法基于随机游走图景,适用于缺乏长期记忆的马尔可夫过程。此类过程的粗粒化行为由扩散方程描述。然而,许多自然过程并不具备马尔可夫性质,而是呈现出反常扩散。我们在此考虑亚扩散过程的情况,它对应于连续时间随机游走,其中一步的等待时间由均值发散的概率分布给出。这样一个过程可被视为在依赖于这种病态等待时间分布的操作时间下从属于正常扩散的过程。我们推导了两种不同但等价的动力学方程形式,对于遵循幂律的等待时间分布,它们可简化为已知的分数扩散或福克 - 普朗克方程。对于非纯幂律的等待时间分布,取决于过程随时间是变慢还是加速,动力学方程的一种或另一种形式具有优势。

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