随机矩阵的渐近循环条件自由性

Pub Date : 2024-01-31 DOI:10.1142/s2010326323500144
Guillaume Cébron, Nicolas Gilliers
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引用次数: 0

摘要

在计算 N×N 随机矩阵上多项式的渐近谱时,Voiculescu 的自由性显现出来,这些矩阵的特征空间位于一般位置:它们被均匀单一随机矩阵 UN 随机旋转。在本文中,我们在前述结果的基础上提出了一种随机矩阵模型,并将其命名为涡旋模型,其中 UN 具有均匀单元随机矩阵的规律,条件是让一个确定性向量 vN 保持不变。在极限 N→+∞ 中,我们证明了由矩阵 UN 随机旋转的 N×N 矩阵在归一化迹和状态向量 vN 方面是渐近无条件的。我们定义了一个称为循环条件自由性的新概念,它 "统一 "了三种独立性:无穷小自由性、循环单调独立性和循环布尔独立性。借助这一新的独立性,可以计算涡旋模型中的无穷小分布。最后,我们详细阐述了涡旋模型,以便为 α 自由性和 βγ 自由性(以前称为缩进独立性和有序自由性)建立随机矩阵模型。
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Asymptotic cyclic-conditional freeness of random matrices

Voiculescu’s freeness emerges when computing the asymptotic spectra of polynomials on N×N random matrices with eigenspaces in generic positions: they are randomly rotated with a uniform unitary random matrix UN. In this paper, we elaborate on the previous result by proposing a random matrix model, which we name the Vortex model, where UN has the law of a uniform unitary random matrix conditioned to leave invariant one deterministic vector vN. In the limit N+, we show that N×N matrices randomly rotated by the matrix UN are asymptotically conditionally free with respect to the normalized trace and the state vector vN. We define a new concept called cyclic-conditional freeness “unifying” three independences: infinitesimal freeness, cyclic-monotone independence and cyclic-Boolean independence. Infinitesimal distributions in the Vortex model can be computed thanks to this new independence. Finally, we elaborate on the Vortex model in order to build random matrix models for α-freeness and for βγ-freeness (formerly named indented independence and ordered freeness).

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