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arxiv: 1302.6539 · v1 · pith:2UJE5FJWnew · submitted 2013-02-26 · 🧮 math.PR

Random truncations of Haar distributed matrices and bridges

classification 🧮 math.PR
keywords processcenteringconvergesdistributedhaarlfloormathbbrandom
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Let $U$ be a Haar distributed matrix in $\mathbb U(n)$ or $\mathbb O (n)$. In a previous paper, we proved that after centering, the two-parameter process \[T^{(n)} (s,t) = \sum_{i \leq \lfloor ns \rfloor, j \leq \lfloor nt\rfloor} |U_{ij}|^2\] converges in distribution to the bivariate tied-down Brownian bridge. In the present paper, we replace the deterministic truncation of $U$ by a random one, where each row (resp. column) is chosen with probability $s$ (resp. $t$) independently. We prove that the corresponding two-parameter process, after centering and normalization by $n^{-1/2}$ converges to a Gaussian process. On the way we meet other interesting convergences.

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