307 research outputs found

    Non-abelian Littlewood-Offord inequalities

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    In 1943, Littlewood and Offord proved the first anti-concentration result for sums of independent random variables. Their result has since then been strengthened and generalized by generations of researchers, with applications in several areas of mathematics. In this paper, we present the first non-abelian analogue of Littlewood-Offord result, a sharp anti-concentration inequality for products of independent random variables.Comment: 14 pages Second version. Dependence of the upper bound on the matrix size in the main results has been remove

    Arak Inequalities for Concentration Functions and the Littlewood--Offord Problem: a shortened version

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    Let X,X1,…,XnX,X_1,\ldots,X_n be independent identically distributed random variables. In this paper we study the behavior of concentration functions of weighted sums ∑k=1nXkak\sum_{k=1}^{n} X_k a_k with respect to the arithmetic structure of coefficients~aka_k in the context of the Littlewood--Offord problem. Concentration results of this type received renewed interest in connection with distributions of singular values of random matrices. Recently, Tao and Vu proposed an Inverse Principle in the Littlewood--Offord problem. We discuss the relations between the Inverse Principle of Tao and Vu as well as that of Nguyen and Vu and a similar principle formulated for sums of arbitrary independent random variables in the work of Arak from the 1980's. This paper is a shortened and edited version of the preprint arXiv:1506.09034. Here we present the results without proofs.Comment: 9 pages. shortened version of arXiv:1506.0903

    Bound for the maximal probability in the Littlewood-Offord problem

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    The paper deals with studying a connection of the Littlewood--Offord problem with estimating the concentration functions of some symmetric infinitely divisible distributions. It is shown that the values at zero of the concentration functions of weighted sums of i.i.d. random variables may be estimated by the values at zero of the concentration functions of symmetric infinitely divisible distributions with the L\'evy spectral measures which are multiples of the sum of delta-measures at ±\pmweights involved in constructing the weighted sums.Comment: 5 page
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