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Random-bond Ising model in two dimensions, the Nishimori line, and supersymmetry

机译:二维随机键Ising模型,Nishimori线,和   超对称

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摘要

We consider a classical random-bond Ising model (RBIM) with binarydistribution of $\pm K$ bonds on the square lattice at finite temperature. Inthe phase diagram of this model there is the so-called Nishimori line whichintersects the phase boundary at a multicritical point. It is known that thecorrelation functions obey many exact identities on this line. We use asupersymmetry method to treat the disorder. In this approach the transfermatrices of the model on the Nishimori line have an enhanced supersymmetryosp($2n+1|2n$), in contrast to the rest of the phase diagram, where thesymmetry is osp($2n|2n$) (where $n$ is an arbitrary positive integer). Ananisotropic limit of the model leads to a one-dimensional quantum Hamiltoniandescribing a chain of interacting superspins, which are irreduciblerepresentations of the osp($2n+1|2n$) superalgebra. By generalizing thissuperspin chain, we embed it into a wider class of models. These include othermodels that have been studied previously in one and two dimensions. We suggestthat the multicritical behavior in two dimensions of a class of thesegeneralized models (possibly not including the multicritical point in the RBIMitself) may be governed by a single fixed point, at which the supersymmetry isenhanced still further to osp($2n+2|2n$). This suggestion is supported by acalculation of the renormalization-group flows for the corresponding nonlinearsigma models at weak coupling.
机译:我们考虑一个经典的随机键伊辛模型(RBIM),在有限的温度下,方格上具有$ \ pm K $键的二元分布。在该模型的相图中,存在所谓的Nishimori线,该线在多临界点处与相边界相交。众所周知,相关函数在这条线上服从许多确切的身份。我们使用超对称方法来治疗该疾病。与相位图的其余部分(其中osp($ 2n | 2n $)的对称性相反)相比,在这种方法中,Nishimori线上的模型的传递矩阵具有增强的supersymmetryosp($ 2n + 1 | 2n $)。 n $是任意正整数)。该模型的各向异性极限导致一维量子哈密顿量,它描述了相互作用的超旋转的链,这些超旋转是osp($ 2n + 1 | 2n $)超代数的不可约表示。通过概括该superspin链,我们将其嵌入到更广泛的模型中。这些包括先前已在一维和二维中研究的其他模型。我们建议,在一类此类广义模型的二维中的多临界行为(可能在RBIMitself中不包括多临界点)可能由单个固定点控制,在该点上,超对称性进一步增强为osp($ 2n + 2 | 2n $)。弱耦合条件下相应非线性sigma模型的重归一化组流量的计算为该建议提供了支持。

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