Phase transition in random walks with long-range correlations.
Phase transition in random walks with long-range correlations.
复制标题
具有长程相关性的随机游走中的相变。
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
U. Keshet
中科院分区：
文献类型：
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作者：
S. Hod;U. Keshet
受相关序列理论最新研究成果的启发，我们分析了具有长期记忆的随机漫步（具有长期相关性的二元链）的动力学。在我们的模型中，二进制字符串中一个单位比特的概率取决于它之前的一致的分数。我们发现，当相关强度超过临界值时，系统经历了一个动态相变，从正常扩散阶段，其中方差D(L)与弦的长度L成比例，到超扩散阶段（D(L)近似于L α， α >1）。我们展示了我们的结果与替代模型的通用性，并讨论了它们对各种数据的适用性，例如粗粒度DNA序列、书面文本和金融数据。
Motivated by recent results in the theory of correlated sequences, we analyze the dynamics of random walks with long-term memory (binary chains with long-range correlations). In our model, the probability for a unit bit in a binary string depends on the fraction of unities preceding it. We show that the system undergoes a dynamical phase transition from normal diffusion, in which the variance D(L) scales as the string's length L, into a superdiffusion phase ( D(L) approximately Lalpha,alpha>1), when the correlation strength exceeds a critical value. We demonstrate the generality of our results with respect to alternative models, and discuss their applicability to various data, such as coarse-grained DNA sequences, written texts, and financial data.
影响因子：
8.6
作者：
Yang, ACC;Hseu, SS;Peng, CK
通讯作者：
Peng, CK