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arXiv math-ph/0505038math-phmath.MP
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随机矩阵的一维随机增长与高斯系综

One-dimensional stochastic growth and Gaussian ensembles of random matrices

Patrik L. Ferrari, Michael Praehofer

摘要:

在这篇综述论文中,我们考虑了多核生长(PNG)模型在一个空间维度和它的关系,随机矩阵合奏。对于弯曲和平坦的增长,表面波动的标度函数与来自随机矩阵的某些高斯系综的极限分布函数相一致。这种连接可以通过与PNG模型和随机矩阵集合相关联的点过程来解释,分别通过对多层PNG和多矩阵模型的扩展。我们还解释了其他模型,相当于PNG模型:定向聚合物,最长的增加子序列的问题,杨tableaux,定向渗流模型,扭结-反扭结气体,和Hammersley过程。

英文摘要:

In this review paper we consider the polynuclear growth (PNG) model in one spatial dimension and its relation to random matrix ensembles. For curved and flat growth the scaling functions of the surface fluctuations coincide with limit distribution functions coming from certain Gaussian ensembles of random matrices. This connection can be explained via point processes associated to the PNG model and the random matrices ensemble by an extension to the multilayer PNG and multi-matrix models, respectively. We also explain other models which are equivalent to the PNG model: directed polymers, the longest increasing subsequence problem, Young tableaux, a directed percolation model, kink-antikink gas, and Hammersley process.

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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