Kim Hyun-Joo
Department of Physics Education, Korea National University of Education, Chungbuk 363-791, Korea.
Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Jul;90(1):012103. doi: 10.1103/PhysRevE.90.012103. Epub 2014 Jul 2.
We introduced simple microscopic non-Markovian walk models which describe the underlying mechanism of anomalous diffusions. In the models, we considered the competitions between randomness and memory effects of previous history by introducing the probability parameters. The memory effects were considered in two aspects: one is the perfect memory of whole history and the other is the latest memory enhanced with time. In the perfect memory model superdiffusion was induced with the relation of the Hurst exponent H to the controlling parameter p as H = p for p>1/2, while in the latest memory enhancement models, anomalous diffusions involving both superdiffusion and subdiffusion were induced with the relations H = (1+α)/2 and H = (1-α)/2 for 0 ≤ α ≤ 1, where α is the parameter controlling the degree of the latest memory enhancement. Also we found that, although the latest memory was only considered, the memory improved with time results in the long-range correlations between steps and the correlations increase as time goes on. Thus we suggest the memory enhancement as a key origin describing anomalous diffusions.
我们引入了简单的微观非马尔可夫行走模型,该模型描述了反常扩散的潜在机制。在这些模型中,我们通过引入概率参数来考虑随机性与先前历史记忆效应之间的竞争。记忆效应从两个方面来考虑:一方面是对整个历史的完美记忆,另一方面是随时间增强的最新记忆。在完美记忆模型中,当赫斯特指数H与控制参数p满足p>1/2时H = p的关系时,会引发超扩散;而在最新记忆增强模型中,当0 ≤ α ≤ 1时,通过H = (1+α)/2和H = (1-α)/2的关系会引发涉及超扩散和亚扩散的反常扩散,其中α是控制最新记忆增强程度的参数。我们还发现,尽管只考虑了最新记忆,但记忆随时间的改善会导致步长之间的长程相关性,且这种相关性会随着时间的推移而增加。因此,我们认为记忆增强是描述反常扩散的关键根源。