arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 0806.2557cond-mat.stat-mechcond-mat.dis-nn
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随机介质中确定性行走中记忆的影响:平均场近似下的解析计算

The influence of memory in deterministic walks in random media: analytical calculation within a mean field approximation

Cesar Augusto Sangaletti Tercariol, Alexandre Souto Martinez

摘要:

考虑由随机分布的点组成的随机介质,使得距离之间没有相关性。这是随机链接模型,它是欧几里得随机点结构的高维极限(平均场近似)。在随机链接模型中,在离散的时间步,步行者移动到最近的网站,这还没有访问在最后$μ$步骤(内存),产生一个确定性的部分自我回避步行(游客步行)。分析得到了具有记忆$μ= 2$的步行者所探索的点的个数$n$的分布,以及瞬时和周期的联合分布。这一结果能够解释$μ= 1$(无记忆,由极值统计驱动)和$μ= 2$(有记忆,由组合统计驱动)之间的探索行为的突然变化。在$μ= 1$情况下,热力学极限$(N \gg 1)$中的平均新访问点正好是$<n > = e = 2.72 ...$,而在$μ= 2$情况下,访问点的平均数量$<n>$与$N^{1/2}$成比例。此外,该结果允许我们稳定具有$μ=2$的随机链路模型和具有$μ=0$的随机映射(不相关的来回距离)之间的等价性,以及瞬态时间为零的情况与非零瞬态时间相比的急剧变化。

英文摘要:

Consider a random medium consisting of points randomly distributed so that there is no correlation among the distances. This is the random link model, which is the high dimensionality limit (mean field approximation) for the euclidean random point structure. In the random link model, at discrete time steps, the walker moves to the nearest site, which has not been visited in the last $μ$ steps (memory), producing a deterministic partially self avoiding walk (the tourist walk). We have obtained analitically the distribution of the number $n$ of points explored by a walker with memory $μ= 2$, as well as the transient and period joint distribution. This result enables to explain the abrupt change in the exploratory behavior between the cases $μ= 1$ (memoryless, driven by extremal statistics) and $μ= 2$ (with memory, driven by combinatorial statistics). In the $μ= 1$ case, the mean newly visited points in the thermodynamic limit $(N \gg 1)$ is just $<n > = e = 2.72 ...$ while in the $μ= 2$ case, the mean number $<n>$ of visited points is proportional to $N^{1/2}$. Also, this result allows us to stabilish an equivalence between the random link model with $μ=2$ and random map (uncorrelated back and forth distances) with $μ=0$ and the drastic change between the cases where the transient time is null compared to non-null transient times.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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