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Related papers: On 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.

Probability · Mathematics 2022-11-15 Friedrich Götze , Andrei Yu. Zaitsev

Let $X,X_1,\ldots,X_n$ be independent identically distributed random variables. In this paper we study the behavior of concentration functions of weighted sums $\sum_{k=1}^{n}X_ka_k $ with respect to the arithmetic structure of coefficients…

Probability · Mathematics 2018-05-22 Friedrich Götze , Andrei Yu. Zaitsev

Let $X,X_1,\ldots,X_n$ be independent identically distributed random variables. In this paper we study the behavior of concentration functions of weighted sums $\sum_{k=1}^{n}a_k X_k$ with respect to the arithmetic structure of coefficients…

Probability · Mathematics 2021-12-03 Yulia S. Eliseeva , Friedrich Götze , Andrei Yu. Zaitsev

Let $X,X_1,\ldots,X_n$ be independent identically distributed random variables. In this paper we study the behavior of concentration functions of weighted sums $\sum_{k=1}^{n} X_k a_k$ with respect to the arithmetic structure of…

Probability · Mathematics 2022-08-04 Yulia S. Eliseeva , Friedrich Götze , Andrei Yu. Zaitsev

Let $X_1,\ldots,X_n$ be independent identically distributed random variables. In this paper we study the behavior of concentration functions of weighted sums $\sum_{k=1}^{n}X_ka_k $ with respect to the arithmetic structure of…

Probability · Mathematics 2023-04-06 Friedrich Götze , Andrei Yu. Zaitsev

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…

Probability · Mathematics 2022-08-04 Andrei Yu. Zaitsev

Let $X,X_1,...,X_n$ be independent identically distributed random variables. In this paper we study the behavior of the concentration functions of the weighted sums $\sum\limits_{k=1}^{n}a_k X_k$ with respect to the arithmetic structure of…

Probability · Mathematics 2015-05-12 Yulia S. Eliseeva , Friedrich Götze , Andrei Yu. Zaitsev

Motivated by the inverse Littlewood-Offord problem for linear forms, we study the concentration of quadratic forms. We show that if this form concentrates on a small ball with high probability, then the coefficients can be approximated by a…

Combinatorics · Mathematics 2011-05-31 Hoi H. Nguyen

We present an extension of the famous Littlewood-Offord problem when Bernoulli distributions are replaced with discrete log-concave distributions. A variant of the Littlewood-Offord problem for arithmetic progressions, as well as an…

Probability · Mathematics 2026-02-19 Arnaud Marsiglietti , James Melbourne

The Littlewood-Offord problem is a classical question in probability theory and discrete mathematics, proposed, firstly by Littlewood and Offord in the 1940s. Given a set $A$ of integer, this problem asks for an upper bound on the…

Combinatorics · Mathematics 2023-08-09 Simone Costa

Consider a random sum $\eta_1 v_1 + ... + \eta_n v_n$, where $\eta_1,...,\eta_n$ are i.i.d. random signs and $v_1,...,v_n$ are integers. The Littlewood-Offord problem asks to maximize concentration probabilities such as $\P(\eta_1 v_1 + ...…

Probability · Mathematics 2007-05-23 Terence Tao , Van Vu

The classical Erd\H{o}s-Littlewood-Offord problem concerns the random variable $X = a_1 \xi_1 + \dots + a_n \xi_n$, where $a_i \in \mathbb{R} \setminus \{0\}$ are fixed and $\xi_i \sim \text{Ber}(1/2)$ are independent. The…

Combinatorics · Mathematics 2020-01-03 Mihir Singhal

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…

Probability · Mathematics 2016-12-23 Mark Rudelson , Roman Vershynin

Let $X_1,\ldots,X_n$ be independent identically distributed random vectors in $\mathbb{R}^d$. We consider upper bounds on $\max_x \mathbb{P}(a_1X_1+\cdots+a_nX_n=x)$ under various restrictions on $X_i$ and the weights $a_i$. When…

Probability · Mathematics 2020-08-04 Tomas Juškevičius , Valentas Kurauskas

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…

Probability · Mathematics 2015-08-07 Pham H. Tiep , Van H. Vu

We prove anti-concentration results for polynomials of independent random variables with arbitrary degree. Our results extend the classical Littlewood-Offord result for linear polynomials, and improve several earlier estimates. We discuss…

Probability · Mathematics 2015-08-11 Raghu Meka , Oanh Nguyen , Van Vu

Let $X,X_1,\ldots,X_n$ be independent identically distributed random variables. The paper deals with the question about the behavior of the concentration function of the random variable $\sum\limits_{k=1}^{n}X_k a_k$ according to the…

Probability · Mathematics 2013-03-19 Yu. S. Eliseeva

Let $X,X_1,...,X_n$ be independent identically distributed random variables. The paper deals with the question about the behavior of the concentration function of the random variable $\sum_{k=1}^{n}a_k X_k$ according to the arithmetic…

Probability · Mathematics 2014-01-07 Yu. S. Eliseeva , A. Yu. Zaitsev

This paper provides a connection between the concentration of a random variable and the distribution of the roots of its probability generating function. Let $X$ be a random variable taking values in $\{0,\ldots,n\}$ with $\mathbb{P}(X =…

Probability · Mathematics 2022-10-10 Marcus Michelen , Julian Sahasrabudhe

Let $\epsilon_1, \dotsc, \epsilon_n$ be i.i.d. Rademacher random variables taking values $\pm 1$ with probability $1/2$ each. Given an integer vector $\boldsymbol{a} = (a_1, \dotsc, a_n)$, its concentration probability is the quantity…

Combinatorics · Mathematics 2019-04-24 Asaf Ferber , Vishesh Jain , Kyle Luh , Wojciech Samotij
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