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The Littlewood-Offord problem and invertibility of random matrices.(English)Zbl 1139.15015

Summary: We prove two basic conjectures on the distribution of the smallest singular value of random \(n\times n\) matrices with independent entries. Under minimal moment assumptions, we show that the smallest singular value is of order \(n^{ - 1/2}\), which is optimal for Gaussian matrices. Moreover, we give an optimal estimate on the tail probability. This comes as a consequence of a new and essentially sharp estimate in the Littlewood-Offord problem: for i.i.d. random variables \(X_k\) and real numbers \(a_k\), determine the probability \(p\) that the sum \(\sum_ka_kX_k\) lies near some number \(v\). For arbitrary coefficients \(a_k\) of the same order of magnitude, we show that they essentially lie in an arithmetic progression of length \(1/p\).

MSC:

15B52 Random matrices (algebraic aspects)
15A18 Eigenvalues, singular values, and eigenvectors

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References:

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This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
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