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arXiv 2109.09221math-phcond-mat.dis-nnhep-thmath.MPmath.PRnlin.CD
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伪厄密随机矩阵模型:一般形式

Pseudo-Hermitian Random Matrix Models: General Formalism

Joshua Feinberg, Roman Riser

摘要:

伪厄米矩阵是关于不定度量的厄米矩阵。它们可以被认为是在Krein空间上定义的伪埃尔米特算子的截断,连同相关的度量,到有限维子空间。因此,在随机矩阵理论的通常精神中,它们可以用来模拟混沌或无序的PT对称量子系统,或它们的增益-损耗平衡的经典类似物,在破缺PT对称的阶段。伪厄米矩阵的特征值要么是实数,要么是复共轭对。在本文中,我们引入了一族伪厄米随机矩阵模型,参数依赖于他们的度量。在大矩阵尺寸$N$的限制下,我们应用图解法得到了它的平均预解式和特征值密度作为度量的显函数。作为一个具体的例子,它本质上是一个非紧酉李代数的元素的合奏,我们选择一个特别简单的一组度量,并计算由此产生的预解式和密度的特征值的封闭形式。该谱由复本征值的有限部分组成,复本征值均匀地占据两个二维斑点,相对于实轴对称,以及实本征值的互补部分,浓缩在有限段中,具有已知的非均匀密度。复特征值和实特征值的数量取决于度量的签名,即其正特征值和负特征值的数量。我们还对这些特定指标的模型进行了全面的数值分析。我们的数值结果迅速收敛到渐近解析大$N$表达式。

英文摘要:

Pseudo-hermitian matrices are matrices hermitian with respect to an indefinite metric. They can be thought of as the truncation of pseudo-hermitian operators, defined over some Krein space, together with the associated metric, to a finite dimensional subspace. As such, they can be used, in the usual spirit of random matrix theory, to model chaotic or disordered PT-symmetric quantum systems, or their gain-loss-balanced classical analogs, in the phase of broken PT-symmetry. The eigenvalues of pseudo-hermitian matrices are either real, or come in complex-conjugate pairs. In this paper we introduce a family of pseudo-hermitian random matrix models, depending parametrically on their metric. We apply the diagrammatic method to obtain its averaged resolvent and density of eigenvalues as explicit functions of the metric, in the limit of large matrix size $N$. As a concrete example, which is essentially an ensemble of elements of the non-compact unitary Lie algebra, we choose a particularly simple set of metrics, and compute the resulting resolvent and density of eigenvalues in closed form. The spectrum consists of a finite fraction of complex eigenvalues, which occupy uniformly two two-dimensional blobs, symmetric with respect to the real axis, as well as the complimentary fraction of real eigenvalues, condensed in a finite segment, with a known non-uniform density. The numbers of complex and real eigenvalues depend on the signature of the metric, that is, the numbers of its positive and negative eigenvalues. We have also carried thorough numerical analysis of the model for these particular metrics. Our numerical results converge rapidly towards the asymptotic analytical large-$N$ expressions.

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