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arXiv 0903.4968cond-mat.stat-mechmath-phmath.MP
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开边界非对称简单排它过程的坐标Bethe矩阵的构造

Construction of a Coordinate Bethe Ansatz for the asymmetric simple exclusion process with open boundaries

Damien Simon

摘要:

具有开放边界的非对称简单排斥过程是一个非常简单的非平衡统计物理模型,它是已知的可积模型。特别是,它的频谱可以用贝特根来描述。电流的大偏差函数也可以通过对角化修改的过渡矩阵来获得,该矩阵仍然是可积的:对于参数的特殊值,这个新矩阵的谱也可以用贝特根来描述。然而,由于在以前的作品中用于写贝特方程的代数框架,激励的性质和特征向量的完整结构仍然是未知的。本文解释了修正转移矩阵的特征向量具有物理相关性的原因,给出了特征向量的显式表达式,并将其应用于非典型电流的研究。它还显示了如何坐标Bethe Anestheted开发的激励导致一个简单的推导Bethe方程和有效性条件,这个Anestheted。恢复了de Gier和Essler得到的所有结果,并给出了例外点的物理解释。本文还讨论了这种方法与其他工具(如矩阵Anglomerator)的重叠。这里提出的方法可能不特定于非对称排除过程,并且可以应用于具有开放边界的其他模型以找到类似的例外点。

英文摘要:

The asymmetric simple exclusion process with open boundaries, which is a very simple model of out-of-equilibrium statistical physics, is known to be integrable. In particular, its spectrum can be described in terms of Bethe roots. The large deviation function of the current can be obtained as well by diagonalizing a modified transition matrix, that is still integrable: the spectrum of this new matrix can be also described in terms of Bethe roots for special values of the parameters. However, due to the algebraic framework used to write the Bethe equations in the previous works, the nature of the excitations and the full structure of the eigenvectors were still unknown. This paper explains why the eigenvectors of the modified transition matrix are physically relevant, gives an explicit expression for the eigenvectors and applies it to the study of atypical currents. It also shows how the coordinate Bethe Ansatz developped for the excitations leads to a simple derivation of the Bethe equations and of the validity conditions of this Ansatz. All the results obtained by de Gier and Essler are recovered and the approach gives a physical interpretation of the exceptional points The overlap of this approach with other tools such as the matrix Ansatz is also discussed. The method that is presented here may be not specific to the asymmetric exclusion process and may be applied to other models with open boundaries to find similar exceptional points.

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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