利用算子协方差来分解网格模型中的缩放维度

Anders W. Sandvik
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引用次数: 0

摘要

在临界晶格模型中,依赖于距离($r$)的相关函数包含幂律$r^{-2\Delta}$,由基本连续场理论的缩放维数$\Delta$所支配。在蒙特卡罗模拟和其他数值方法中,可以通过数据拟合来提取前导维度,但当两个或更多幂有显著贡献时,这可能会很困难。这里开发了一种利用多个晶格算子之间协方差的方法,其中协方差矩阵的 $r$ 相关特征值代表单个场算子的标度。该方法在二维三临界布卢姆-卡佩尔模型中的对称算子上进行了测试,其中两个相关维度以及一些无关维度连同其相应的特征向量被分离出来。该方法将广泛应用于多临界点的经典和量子模型研究,以及针对简单临界点(或多临界点)的相关算子的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using operator covariance to disentangle scaling dimensions in lattice models
In critical lattice models, distance ($r$) dependent correlation functions contain power laws $r^{-2\Delta}$ governed by scaling dimensions $\Delta$ of an underlying continuum field theory. In Monte Carlo simulations and other numerical approaches, the leading dimensions can be extracted by data fitting, which can be difficult when two or more powers contribute significantly. Here a method utilizing covariance between multiple lattice operators is developed where the $r$ dependent eigenvalues of the covariance matrix represent scaling dimensions of individual field operators. The scheme is tested on symmetric operators in the two-dimensional tricritical Blume-Capel model, where the two relevant dimensions, as well as some irrelevant ones, are isolated along with their corresponding eigenvectors. The method will be broadly useful in studies of classical and quantum models at multicritical points and for targeting irrelevant operators at simple critical (or multicritical) points.
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