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The study of the generalized Hamming weight of linear codes is a significant research topic in coding theory as it conveys the structural information of the codes and determines their performance in various applications. However,…

Information Theory · Computer Science 2023-10-19 Chao Liu , Dabin Zheng , Wei Lu , Xiaoqiang Wang

Let $Y$ be a standard Gamma(k) distributed random variable, $k>0$, and let $X$ be an independent positive random variable. We prove that if $X$ has a hyperbolically monotone density of order $k$ ($HM_k$), then the distributions of $Y\cdot…

Probability · Mathematics 2019-02-20 Tord Sjödin

The standard $(n, k, d)$ model of random groups is a model where the relators are chosen randomly from the set of cyclically reduced words of length $k$ on an $n$-element generating set. Gromov's density model of random groups considers the…

Group Theory · Mathematics 2017-11-22 C. J. Ashcroft , Colva M. Roney-Dougal

A statistical estimation algorithm of the weight distribution of a linear code is shown, based on using its generator matrix as a compression function on random bit strings.

Information Theory · Computer Science 2018-06-07 Alessandro Tomasi , Alessio Meneghetti

By well known results of probability theory, any sequence of random variables with bounded second moments has a subsequence satisfying the central limit theorem and the law of the iterated logarithm in a randomized form. In this paper we…

Probability · Mathematics 2017-07-28 I. Berkes , R. Tichy

A codeword is associated to a linearized polynomial. The weight distribution of the codewords is determined as the linearized polynomial varies in a family of fixed degree. There is a corresponding result on Wenger graphs from linearized…

Information Theory · Computer Science 2015-02-17 Haode Yan , Chunlei Liu

We revisit the random allocation model in which $n$ balls are independently placed into $N$ boxes with probabilities $q_1,\ldots,q_N$. A classical asymptotic result due to Kolchin, Sevastyanov, and Chistyakov for the expectations,…

Probability · Mathematics 2026-04-28 Serik Sagitov

The Generalized Hamming weights and their relative version, which generalize the minimum distance of a linear code, are relevant to numerous applications, including coding on the wire-tap channel of type II, $t$-resilient functions,…

Information Theory · Computer Science 2024-11-21 Eduardo Camps-Moreno , Hiram H. López , Gretchen L. Matthews , Rodrigo San-José

This paper deals with an improvement of the "a-priori stability bounds" on the variation of the action variables and on the stability time obtained from a given Birkhoff normal form around the elliptic equilibrium point of an Hamiltonian…

Dynamical Systems · Mathematics 2026-01-27 Massimiliano Guzzo , Chiara Caracciolo , Gabriella Pinzari

We present nonasymptotic concentration inequalities for sums of independent and identically distributed random variables that yield asymptotic strong Gaussian approximations of Koml\'os, Major, and Tusn\'ady (KMT) [1975,1976]. The constants…

Probability · Mathematics 2025-10-01 Ian Waudby-Smith , Martin Larsson , Aaditya Ramdas

We prove that the $k$-th positive integer moment of partial sums of Steinhaus random multiplicative functions over the interval $(x, x+H]$ matches the corresponding Gaussian moment, as long as $H\ll x/(\log x)^{2k^2+2+o(1)}$ and $H$ tends…

Number Theory · Mathematics 2024-02-20 Mayank Pandey , Victor Y. Wang , Max Wenqiang Xu

We calculate the expectation value of an arbitrary product of characteristic polynomials of complex random matrices and their hermitian conjugates. Using the technique of orthogonal polynomials in the complex plane our result can be written…

High Energy Physics - Theory · Physics 2010-04-05 G. Akemann , G. Vernizzi

Rank 1 inhomogeneous random graphs are a natural generalization of Erd\H{o}s R\'enyi random graphs. In this generalization each node is given a weight. Then the probability that an edge is present depends on the product of the weights of…

Probability · Mathematics 2021-07-28 Othmane Safsafi

Diaconis and Griffiths (2014) study the multivariate Krawtchouk polynomials orthogonal on the multinomial distribution. In this paper we derive the reproducing kernel orthogonal polynomials Q_n(x,y};N,p) on the multinomial distribution…

Probability · Mathematics 2019-02-06 Persi Diaconis , Robert Griffiths

We prove a rigidity theorem for the geometry of the unit ball in random subspaces of the scl norm in B_1^H of a free group. In a free group F of rank k, a random word w of length n (conditioned to lie in [F,F]) has scl(w)=log(2k-1)n/6log(n)…

Group Theory · Mathematics 2013-07-09 Danny Calegari , Alden Walker

Let $\Gamma$ be a nonelementary hyperbolic group with a word metric $d$ and $\partial\Gamma$ its hyperbolic boundary equipped with a visual metric $d_a$ for some parameter $a>1$. Fix a superexponential symmetric probability $\mu$ on…

Probability · Mathematics 2020-07-28 Vladas Sidoravicius , Longmin Wang , Kainan Xiang

In this paper, we investigate the large deviations of sums of weighted random variables that are approximately independent, generalizing and improving some of the results of Montgomery and Odlyzko. We are motivated by examples arising from…

Number Theory · Mathematics 2021-05-05 Andrew Granville , Youness Lamzouri

Given a large set $U$ where each item $a\in U$ has weight $w(a)$, we want to estimate the total weight $W=\sum_{a\in U} w(a)$ to within factor of $1\pm\varepsilon$ with some constant probability $>1/2$. Since $n=|U|$ is large, we want to do…

Data Structures and Algorithms · Computer Science 2021-10-29 Lorenzo Beretta , Jakub Tětek

In classical statistics and distribution testing, it is often assumed that elements can be sampled from some distribution $P$, and that when an element $x$ is sampled, the probability $P$ of sampling $x$ is also known. Recent work in…

Data Structures and Algorithms · Computer Science 2022-08-03 Talya Eden , Jakob Bæk Tejs Houen , Shyam Narayanan , Will Rosenbaum , Jakub Tětek

A large set of signals can sometimes be described sparsely using a dictionary, that is, every element can be represented as a linear combination of few elements from the dictionary. Algorithms for various signal processing applications,…

Machine Learning · Statistics 2013-02-06 Daniel Vainsencher , Shie Mannor , Alfred M. Bruckstein