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arXiv 1502.07374math.PRcond-mat.stat-mechmath-phmath.MPnlin.SI
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线上随机高自旋顶点模型

Stochastic higher spin vertex models on the line

Ivan Corwin, Leonid Petrov

摘要:

我们在线引入了一个四参数相互作用粒子系统族,它可以通过一组完整的Bethe ansatz本征函数显式对角化,并且具有某些Markov对偶性。在此基础上,对于分步初始数据的系统,给出了矩的嵌套围道积分公式和拉普拉斯型变换的弗雷德霍姆行列式公式。通过对参数的各种选择或限制,这个族退化为Kardar-Parisi-Zhang普适类中的许多已知的精确可解模型,并导致许多新的此类模型的例子。特别是,ASEP,随机六顶点模型,q-TASEP和各种定向聚合物模型都以这种方式出现。我们的系统是从随机版本的R-矩阵相关的六顶点模型。这里使用的关键工具之一是R-矩阵的融合,我们提供了这个过程的概率证明。

英文摘要:

We introduce a four-parameter family of interacting particle systems on the line which can be diagonalized explicitly via a complete set of Bethe ansatz eigenfunctions, and which enjoy certain Markov dualities. Using this, for the systems started in step initial data we write down nested contour integral formulas for moments and Fredholm determinant formulas for Laplace-type transforms. Taking various choices or limits of parameters, this family degenerates to many of the known exactly solvable models in the Kardar-Parisi-Zhang universality class, as well as leads to many new examples of such models. In particular, ASEP, the stochastic six-vertex model, q-TASEP and various directed polymer models all arise in this manner. Our systems are constructed from stochastic versions of the R-matrix related to the six-vertex model. One of the key tools used here is the fusion of R-matrices and we provide a probabilistic proof of this procedure.

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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