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arxiv: 1102.1476 · v2 · pith:7J7GA3NNnew · submitted 2011-02-08 · 🧮 math.CO · math.PR

On the least singular value of random symmetric matrices

classification 🧮 math.CO math.PR
keywords matrixrandomsymmetricentriesgammawhoseassumptionbounded
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Let $F_n$ be an $n$ by $n$ symmetric matrix whose entries are bounded by $n^{\gamma}$ for some $\gamma>0$. Consider a randomly perturbed matrix $M_n=F_n+X_n$, where $X_n$ is a random symmetric matrix whose upper diagonal entries $x_{ij}$ are iid copies of a random variable $\xi$. Under a very general assumption on $\xi$, we show that for any $B>0$ there exists $A>0$ such that $P(\sigma_n(M_n)\le n^{-A})\le n^{-B}$. The proof uses an inverse-type result concerning concentration of quadratic forms, which is of interest of its own.

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