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We prove that the local eigenvalue statistics for $d=1$ random band matrices with fixed bandwidth and, for example, Gaussian entries, is given by a Poisson point process and we identify the intensity of the process. The proof relies on an…

Mathematical Physics · Physics 2020-09-01 Benjamin Brodie , Peter D. Hislop

We use Stein's method to obtain bounds on the rate of convergence for a class of statistics in geometric probability obtained as a sum of contributions from Poisson points which are exponentially stabilizing, i.e. locally determined in a…

Probability · Mathematics 2007-05-23 Mathew D. Penrose , J. E. Yukich

Weighted automata over the nonnegative reals form a fundamental model for quantitative languages. We show that, up to scaling, this model collapses to probabilistic automata. Concretely, we prove that every weighted automaton whose…

Formal Languages and Automata Theory · Computer Science 2026-03-02 Smayan Agarwal , Aalok Thakkar

Consider the following partial "sorting algorithm" on permutations: take the first entry of the permutation in one-line notation and insert it into the position of its own value. Continue until the first entry is 1. This process imposes a…

Probability · Mathematics 2017-02-17 Tobias Johnson , Anne Schilling , Erik Slivken

We consider a finite sequence of random points in a finite domain of a finite-dimensional Euclidean space. The points are sequentially allocated in the domain according to a model of cooperative sequential adsorption. The main peculiarity…

Probability · Mathematics 2009-11-11 V. Shcherbakov

We consider the problem of estimating the total probability of all symbols that appear with a given frequency in a string of i.i.d. random variables with unknown distribution. We focus on the regime in which the block length is large yet no…

Information Theory · Computer Science 2016-11-15 Aaron B. Wagner , Pramod Viswanath , Sanjeev R. Kulkarni

In this paper, we study a class of multiscale McKean-Vlasov stochastic systems where the entire system depends on the distribution of the fast component. First of all, by the Poisson equation method we prove that the slow component…

Probability · Mathematics 2025-09-30 Jie Xiang , Huijie Qiao

Small-world networks, known for high local clustering and short path lengths, are a fundamental structure in many real-world systems, including social, biological, and technological networks. We apply the theory of (marked) local…

Probability · Mathematics 2026-04-29 Yeganeh Alimohammadi , Senem Işık , Amin Saberi

A locally testable language L is a language with the property that for some non negative integer k, called the order or the level of local testable, whether or not a word u in the language L depends on (1) the prefix and the suffix of the…

Formal Languages and Automata Theory · Computer Science 2020-11-13 A. N. Trahtman

Many spatial models exhibit locality structures that effectively reduce their intrinsic dimensionality, enabling efficient approximation and sampling of high-dimensional distributions. However, existing approximation techniques primarily…

Machine Learning · Statistics 2026-02-02 Tiangang Cui , Shuigen Liu , Xin T. Tong

Consider a stochastic process $\mathfrak{X}$, regenerative at a state $x$ which is instantaneous and regular. Let $L$ be a regenerative local time for $\mathfrak{X}$ at $x$. Suppose furthermore that $\mathfrak{X}$ can be approximated by…

Probability · Mathematics 2019-10-22 Aleksandar Mijatović , Gerónimo Uribe Bravo

Consider the sample covariance matrix $$\Sigma^{1/2}XX^T\Sigma^{1/2}$$ where $X$ is an $M\times N$ random matrix with independent entries and $\Sigma$ is an $M\times M$ diagonal matrix. It is known that if $\Sigma$ is deterministic, then…

Probability · Mathematics 2023-02-27 Ji Oon Lee , Yiting Li

This paper analyzes a stochastic logistic difference equation under the assumption that the population distribution follows a normal distribution. Our focus is on the mathematical relationship between the average growth rate and a newly…

Probability · Mathematics 2025-04-22 Haiyan Wang

We consider a Markov chain $\{X_n\}_{n=0}^\8$ on $\R^d$ defined by the stochastic recursion $X_{n}=M_n X_{n-1}+Q_n$, where $(Q_n,M_n)$ are i.i.d. random variables taking values in the affine group $H=\R^d\rtimes {\rm GL}(\R^d)$. Assume that…

Probability · Mathematics 2008-11-10 Dariusz Buraczewski , Ewa Damek , Yves Guivarc'h

The Lov\'{a}sz Local Lemma (LLL) says that, given a set of bad events that depend on the values of some random variables and where each event happens with probability at most $p$ and depends on at most $d$ other events, there is an…

Data Structures and Algorithms · Computer Science 2019-08-21 Sebastian Brandt , Yannic Maus , Jara Uitto

We characterize the convergence in distribution to a standard normal law for a sequence of multiple stochastic integrals of a fixed order with variance converging to 1. Some applications are given, in particular to study the limiting…

Probability · Mathematics 2007-05-23 David Nualart , Giovanni Peccati

Doron Gepner's word statistics, that came up in his research in conformal field theory, is studied and it is conjectured that its scaled limiting distribution is the Logistic distribution. We support this by proving rigorously that the…

Combinatorics · Mathematics 2016-04-05 Doron Zeilberger

We present a theoretical and empirical investigation of the statistical behaviour of the words in a text produced by human language. To this aim, we analyse the word distribution of various texts of Italian language selected from a specific…

Neurons and Cognition · Quantitative Biology 2025-04-15 Diederik Aerts , Jonito Aerts Arguëlles , Lester Beltran , Massimiliano Sassoli de Bianchi , Sandro Sozzo

Asymptotical behavior of the distribution function of local density of states (LDOS) in disordered metallic samples is studied with making use of the supersymmetric $\sigma$--model approach, in combination with the saddle--point method. The…

Condensed Matter · Physics 2009-10-28 A. D. Mirlin

The generative nature of Large Language Models (LLMs) is reflected in the conditional probabilities they compute to sample each response token given the previous tokens. These probabilities encode the distributional structure that the model…

Computation and Language · Computer Science 2026-05-22 Shilpika Shilpika , Carlo Graziani , Bethany Lusch , Venkatram Vishwanath , Michael E. Papka
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