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arxiv: 1808.04862 · v1 · pith:LIGZJSPPnew · submitted 2018-08-14 · 🧮 math.PR · math.FA

Sanov-type large deviations in Schatten classes

classification 🧮 math.PR math.FA
keywords matrixlambdameasurerandomtimesclassesdeviationseigenvalues
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Denote by $\lambda_1(A), \ldots, \lambda_n(A)$ the eigenvalues of an $(n\times n)$-matrix $A$. Let $Z_n$ be an $(n\times n)$-matrix chosen uniformly at random from the matrix analogue to the classical $\ell_ p^n$-ball, defined as the set of all self-adjoint $(n\times n)$-matrices satisfying $\sum_{k=1}^n |\lambda_k(A)|^p\leq 1$. We prove a large deviations principle for the (random) spectral measure of the matrix $n^{1/p} Z_n$. As a consequence, we obtain that the spectral measure of $n^{1/p} Z_n$ converges weakly almost surely to a non-random limiting measure given by the Ullman distribution, as $n\to\infty$. The corresponding results for random matrices in Schatten trace classes, where eigenvalues are replaced by the singular values, are also presented.

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