Ergodic properties of continuous-time random walks: Finite-size effects and ensemble dependences

被引:40
作者
Miyaguchi, Tomoshige [1 ]
Akimoto, Takuma [2 ]
机构
[1] Naruto Univ Educ, Dept Math Educ, Tokushima 7728502, Japan
[2] Keio Univ, Dept Mech Engn, Yokohama, Kanagawa 2238522, Japan
来源
PHYSICAL REVIEW E | 2013年 / 87卷 / 03期
关键词
ANOMALOUS DIFFUSION; SCALING PROPERTIES; LATERAL DIFFUSION; DYNAMICS; CONVERGENCE;
D O I
10.1103/PhysRevE.87.032130
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
The effects of spatial confinements and smooth cutoffs of the waiting time distribution in continuous-time random walks are studied analytically. We also investigate dependences of ergodic properties on initial ensembles (i.e., distributions of the first waiting time). Here, we consider two ensembles: the equilibrium and a typical nonequilibrium ensemble. For both ensembles, it is shown that the time-averaged mean square displacement (TAMSD) exhibits a crossover from normal to anomalous diffusion due to the spatial confinement and this crossover does not vanish even in the long measurement time limit. Moreover, for the nonequilibrium ensemble, we show that the probability density function of the diffusion constant of TAMSD follows the transient Mittag-Leffler distribution, and that scatter in the TAMSD shows a clear transition from weak ergodicity breaking (an irreproducible regime) to ordinary ergodic behavior (a reproducible regime) as the measurement time increases. This convergence to ordinary ergodicity requires a long measurement time compared to common distributions such as the exponential distribution; in other words, the weak ergodicity breaking persists for a long time. In addition, it is shown that, aside from the TAMSD, a class of observables also exhibits this slow convergence to ergodicity. We also point out that, even though the system with the equilibrium initial ensemble shows no aging, its behavior is quite similar to that for the nonequilibrium ensemble. DOI: 10.1103/PhysRevE.87.032130
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页数:16
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