矩形随机矩阵、相关自由熵和自由Fisher信息
Rectangular random matrices, related free entropy and free Fisher's information
摘要:
我们证明了独立的矩形随机矩阵,当嵌入到一个空间的较大的方阵,是渐近自由的合并在一个可交换的有限维子代数$D$(在酉不变的假设下)。然后考虑包含$D$的有限vonNeumann代数的元素,这些元素在$D$中具有核和范围投影。我们将它们与自由熵的微观状态的方法,和一个自由的Fisher的信息与共轭变量的方法。这两种方法都产生了最优化问题,其解决方案涉及$D$上的自由度和合并。这可能是用自由概率工具研究不同希尔伯特空间之间的算子的第一个命题。作为应用,我们证明了$R$的极式分解的两个部分--具有非平凡核的对角元--之间的自由性和融合性。
英文摘要:
We prove that independent rectangular random matrices, when embedded in a space of larger square matrices, are asymptotically free with amalgamation over a commutative finite dimensional subalgebra $D$ (under an hypothesis of unitary invariance). Then we consider elements of a finite von Neumann algebra containing $D$, which have kernel and range projection in $D$. We associate them a free entropy with the microstates approach, and a free Fisher's information with the conjugate variables approach. Both give rise to optimization problems whose solutions involve freeness with amalgamation over $D$. It could be a first proposition for the study of operators between different Hilbert spaces with the tools of free probability. As an application, we prove a result of freeness with amalgamation between the two parts of the polar decomposition of $R$-diagonal elements with non trivial kernel.
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