...
首页> 外文期刊>Annals of Physics >From quantum mechanics to classical statistical physics: Generalized Rokhsar-Kivelson Hamiltonians and the 'Stochastic Matrix Form' decomposition
【24h】

From quantum mechanics to classical statistical physics: Generalized Rokhsar-Kivelson Hamiltonians and the 'Stochastic Matrix Form' decomposition

机译:从量子力学到经典统计物理学:广义Rokhsar-Kivelson哈密顿量和“随机矩阵形式”分解

获取原文
获取原文并翻译 | 示例
           

摘要

Quantum Hamiltonians that are fine-tuned to their so-called Rokhsar-Kivelson (RK) points, first presented in the context of quantum dimer models, are defined by their representations in preferred bases in which their ground state wave functions are intimately related to the partition functions of combinatorial problems of classical statistical physics. We show that all the known examples of quantum Hamiltonians, when fine-tuned to their RK points, belong to a larger class of real, symmetric, and irreducible matrices that admit what we dub a Stochastic Matrix Form (SMF) decomposition. Matrices that are SMF decomposable are shown to be in one-to-one correspondence with stochastic classical systems described by a Master equation of the matrix type, hence their name. It then follows that the equilibrium partition function of the stochastic classical system partly controls the zero-temperature quantum phase diagram, while the relaxation rates of the stochastic classical system coincide with the excitation spectrum of the quantum problem. Given a generic quantum Hamiltonian construed as an abstract operator defined on some Hilbert space, we prove that there exists a continuous manifold of bases in which the representation of the quantum Hamiltonian is SMF decomposable, i.e., there is a (continuous) manifold of distinct stochastic classical systems related to the same quantum problem. Finally, we illustrate with three examples of Hamiltonians fine-tuned to their RK points, the triangular quantum dimer model, the quantum eight-vertex model, and the quantum three-coloring model on the honeycomb lattice, how they can be understood within our framework, and how this allows for immediate generalizations, e.g., by adding non-trivial interactions to these models. (c) 2005 Elsevier Inc. All rights reserved.
机译:精细地调整到所谓的Rokhsar-Kivelson(RK)点的量子哈密顿量,首先在量子二聚体模型的背景下出现,由它们在优选基中的表示形式定义,在这些优选基中,基态波函数与基态波函数密切相关。古典统计物理组合问题的分区函数。我们证明,所有量子哈密顿量的已知例子,当微调到它们的RK点时,都属于一类更大的实,对称和不可约矩阵,它们接受了我们所谓的随机矩阵形式(SMF)分解。可分解为SMF的矩阵显示为与矩阵类型的Master方程描述的随机经典系统一一对应,因此得名。因此,随机经典系统的平衡分配函数部分地控制了零温量子相图,而随机经典系统的弛豫率与量子问题的激发谱一致。给定被解释为在某个希尔伯特空间上定义的抽象算子的一般量子哈密顿量,我们证明存在一个连续的基流形,其中量子哈密顿量的表示是可分解的SMF,即,存在一个(不同的)随机随机数(连续)与同一量子问题有关的经典系统。最后,我们通过蜂窝网格上的三个哈密顿量示例(分别调整为RK点),三角形量子二聚体模型,量子八顶点模型和量子三色模型来说明它们如何在我们的框架中理解,以及如何通过将非平凡的交​​互添加到这些模型来立即进行概括。 (c)2005 Elsevier Inc.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号