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具有超重型尾等待时间和重型尾跳跃长度分布的解耦连续时间随机游走的渐近解。

Asymptotic solutions of decoupled continuous-time random walks with superheavy-tailed waiting time and heavy-tailed jump length distributions.

作者信息

Denisov S I, Yuste S B, Bystrik Yu S, Kantz H, Lindenberg K

机构信息

Sumy State University, Rimsky-Korsakov Street 2, UA-40007 Sumy, Ukraine.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Dec;84(6 Pt 1):061143. doi: 10.1103/PhysRevE.84.061143. Epub 2011 Dec 27.

Abstract

We study the long-time behavior of decoupled continuous-time random walks characterized by superheavy-tailed distributions of waiting times and symmetric heavy-tailed distributions of jump lengths. Our main quantity of interest is the limiting probability density of the position of the walker multiplied by a scaling function of time. We show that the probability density of the scaled walker position converges in the long-time limit to a nondegenerate one only if the scaling function behaves in a certain way. This function as well as the limiting probability density are determined in explicit form. Also, we express the limiting probability density which has heavy tails in terms of the Fox H function and find its behavior for small and large distances.

摘要

我们研究了由等待时间的超重型尾分布和跳跃长度的对称重型尾分布所表征的解耦连续时间随机游走的长期行为。我们主要感兴趣的量是步行者位置的极限概率密度乘以时间的缩放函数。我们表明,仅当缩放函数以某种方式表现时,缩放后的步行者位置的概率密度在长时间极限下才收敛到一个非退化的概率密度。该函数以及极限概率密度以显式形式确定。此外,我们用福克斯H函数表示具有重型尾的极限概率密度,并找出其在小距离和大距离时的行为。

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