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We consider the universality of the nearest neighbour eigenvalue spacing distribution in invariant random matrix ensembles. Focussing on orthogonal and symplectic invariant ensembles, we show that the empirical spacing distribution…

Probability · Mathematics 2015-01-23 Kristina Schubert

We develop a new formulation of Stein's method to obtain computable upper bounds on the total variation distance between the geometric distribution and a distribution of interest. Our framework reduces the problem to the construction of a…

Probability · Mathematics 2013-03-21 Erol A. Peköz , Adrian Röllin , Nathan Ross

A limit theorem for the largest interpoint distance of $p$ independent and identically distributed points in $\mathbb{R}^n$ to the Gumbel distribution is proved, where the number of points $p=p_n$ tends to infinity as the dimension of the…

Probability · Mathematics 2024-02-13 Johannes Heiny , Carolin Kleemann

The total variation distance is a metric of central importance in statistics and probability theory. However, somewhat surprisingly, questions about computing it algorithmically appear not to have been systematically studied until very…

Data Structures and Algorithms · Computer Science 2025-03-17 Arnab Bhattacharyya , Weiming Feng , Piyush Srivastava

Let $ \nu $ be a probability distribution over the linear semi-group $ \mathrm{End}(E) $ for $ E $ a finite dimensional vector space over a locally compact field. We assume that $ \nu $ is proximal, strongly irreducible and that $…

Probability · Mathematics 2025-02-14 Axel Péneau

We study existence and nonexistence of diagonal and separating coordinates for Riemannian symmetric spaces of rank 1. We generalize the results of Gauduchon and Moroianu, 2020, by showing that a symmetric space of rank 1 has diagonal…

Differential Geometry · Mathematics 2025-04-08 Alexey Bolsinov , Holger R. Dullin , Vladimir. S. Matveev , Yury Nikolayevsky

Total variation distance (TV distance) is a fundamental notion of distance between probability distributions. In this work, we introduce and study the problem of computing the TV distance of two product distributions over the domain…

Data Structures and Algorithms · Computer Science 2023-08-21 Arnab Bhattacharyya , Sutanu Gayen , Kuldeep S. Meel , Dimitrios Myrisiotis , A. Pavan , N. V. Vinodchandran

Let $C$ be an $[n,k]$ linear code chosen uniformly at random over a finite field $\mathbb{F}_q$ of size $q$. The following asymptotic probability of $C$ being maximum distance separable (MDS) as $q,n,k\to\infty$ is known: If…

Information Theory · Computer Science 2026-05-01 Rathinakumar Appuswamy , Marco Bazzani , Spencer Congero , Joseph Connelly , Matthew Ekaireb , Kenneth Zeger

Minimizing the Euclidean distance to a set arises frequently in applications. When the set is algebraic, a measure of complexity of this optimization problem is its number of critical points. In this paper we provide a general framework to…

Optimization and Control · Mathematics 2015-06-17 Dmitriy Drusvyatskiy , Hon-Leung Lee , Rekha R. Thomas

This note establishes that if a sequence $P_n, n=1,\ldots$ of probability measures converges in total variation to the limiting probability measure $P$, and $\sigma$-algebras $\mathbb{A}$ and $\mathbb{B}$ are conditionally independent given…

Probability · Mathematics 2024-01-15 Steffen Lauritzen

This paper is motivated by basic complexity and probability questions about permanents of random matrices over finite fields, and in particular, about properties separating the permanent and the determinant. Fix $q = p^m$ some power of an…

Computational Complexity · Computer Science 2025-12-05 Fatemeh Ghasemi , Gal Gross , Swastik Kopparty

We calculate analytically the probability of large deviations from its mean of the largest (smallest) eigenvalue of random matrices belonging to the Gaussian orthogonal, unitary and symplectic ensembles. In particular, we show that the…

Statistical Mechanics · Physics 2009-11-11 David S. Dean , Satya N. Majumdar

Let $Q_n$ be a random $n\times n$ matrix with entries in $\{0,1\}$ whose rows are independent vectors of exactly $n/2$ zero components. We show that the smallest singular value $s_n(Q_n)$ of $Q_n$ satisfies \[ \mathbb{P}\Big\{s_n(Q_n)\le…

Probability · Mathematics 2020-11-02 Tuan Tran

Labelled Markov chains (LMCs) are widely used in probabilistic verification, speech recognition, computational biology, and many other fields. Checking two LMCs for equivalence is a classical problem subject to extensive studies, while the…

Logic in Computer Science · Computer Science 2014-05-16 Taolue Chen , Stefan Kiefer

We are interested in the estimation of the distance in total variation $$ \Delta := \|P_{f(X)} - P_{g(X)}\|_{\mathrm var} $$ between distributions of random variables $f(X)$ and $g(X)$ in terms of proximity of $f$ and $g.$ We propose a…

Probability · Mathematics 2017-06-21 Youri Davydov

We show that, for a constant-degree algebraic curve $\gamma$ in $\mathbb{R}^D$, every set of $n$ points on $\gamma$ spans at least $\Omega(n^{4/3})$ distinct distances, unless $\gamma$ is an {\it algebraic helix} (see Definition 1.1). This…

Metric Geometry · Mathematics 2020-09-16 Orit E. Raz

We study the relation between the total variation (TV) and Hellinger distances between two Gaussian location mixtures. Our first result establishes a general upper bound: for any two mixing distributions supported on a compact set, the…

Statistics Theory · Mathematics 2026-05-27 Joonhyuk Jung , Chao Gao

We prove a $pre$-$asymptotic$ bound on the total variation distance between the uniform distribution over two types of undirected graphs with $n$ nodes. One distribution places a prescribed number of $k_T$ triangles and $k_S$ edges not…

Probability · Mathematics 2015-09-30 Stephen DeSalvo , M. Puck Rombach

Let $X_1,\dots, X_n$ be independent and identically distributed random vectors in $\mathbb{R}^d$. Suppose $\mathbb{E} X_1=0$, $\mathrm{Cov}(X_1)=I_d$, where $I_d$ is the $d\times d$ identity matrix. Suppose further that there exist positive…

Probability · Mathematics 2021-11-02 Xiao Fang , Song-Hao Liu , Qi-Man Shao

In this note, we study the Gaussian fluctuations for the Wishart matrices $d^{-1}\mathcal{X}_{n, d}\mathcal{X}^{T}_{n, d}$, where $\mathcal{X}_{n, d}$ is a $n\times d$ random matrix whose entries are jointly Gaussian and correlated with row…

Probability · Mathematics 2021-04-01 Ivan Nourdin , Fei Pu