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We study the fluctuations of the eigenvalues of real valued large centrosymmetric random matrices via its linear eigenvalue statistic. This is essentially a central limit theorem (CLT) for sums of dependent random variables. The dependence…

Probability · Mathematics 2025-10-01 Indrajit Jana , Sunita Rani

We establish the quenched local limit theorem for reversible random walk on $\Z^d$ (with $d\ge 2$) among stationary ergodic random conductances that permit jumps of arbitrary length. The proof is based on the weak parabolic Harnack…

Probability · Mathematics 2024-04-11 Xin Chen , Takashi Kumagai , Jian Wang

We prove a quenched functional central limit theorem (quenched FCLT) for the sums of a random field (r.f.) along a 2d-random walk in different situations: when the r.f. is iid with a second order moment (random sceneries), or when it is…

Probability · Mathematics 2019-08-13 Guy Cohen , Jean-Pierre Conze

In this paper, we study the Exponential Random Graph Models (ERGMs) conditioning on the number of edges. In subcritical region of model parameters, we prove a conditional Central Limit Theorem (CLT) with explicit mean and variance for the…

Probability · Mathematics 2025-06-19 Xiao Fang , Song-Hao Liu , Zhonggen Su , Xiaolin Wang

We produce a series of Central Limit Theorems (CLTs) associated to compact metric measure spaces $(K,d,\eta)$, with $\eta$ a reasonable probability measure. For the first CLT, we can ignore $\eta$ by isometrically embedding $K$ into…

Probability · Mathematics 2020-01-14 Steven Rosenberg , Jie Xu

We show that there exists a very natural, superstatistics-linked extension of the central limit theorem (CLT) to deformed exponentials (also called q-Gaussians): This generalization favorably compares with the one provided by S. Umarov and…

Statistical Mechanics · Physics 2007-06-04 C. Vignat , A. Plastino

Recent theoretical works have characterized the dynamics of wide shallow neural networks trained via gradient descent in an asymptotic mean-field limit when the width tends towards infinity. At initialization, the random sampling of the…

Probability · Mathematics 2022-03-29 Zhengdao Chen , Grant M. Rotskoff , Joan Bruna , Eric Vanden-Eijnden

Combining cross-section and time series data is a long and well established practice in empirical economics. We develop a central limit theory that explicitly accounts for possible dependence between the two data sets. We focus on common…

Methodology · Statistics 2022-09-20 Jinyong Hahn , Guido Kuersteiner , Maurizio Mazzocco

We consider point-to-point directed paths in a random environment on the two-dimensional integer lattice. For a general independent environment under mild assumptions we show that the quenched energy of a typical path satisfies a central…

Probability · Mathematics 2023-11-30 H. Christian Gromoll , Mark W. Meckes , Leonid Petrov

The standard Large Deviation Theory (LDT) is mathematically illustrated by the Boltzmann-Gibbs factor which describes the thermal equilibrium of short-range-interacting many-body Hamiltonian systems, the velocity distribution of which is…

Statistical Mechanics · Physics 2021-12-24 Ugur Tirnakli , Constantino Tsallis , Nihat Ay

In this paper we provide an asymptotic theory for the symmetric version of the Kullback--Leibler (KL) divergence. We define a estimator for this divergence and study its asymptotic properties. In particular, we prove Law of Large Numbers…

Probability · Mathematics 2024-01-31 Helder Rojas , Artem Logachov

We prove a quenched local central limit theorem for continuous-time random walks in $\mathbb Z^d, d\ge 2$, in a uniformly-elliptic time-dependent balanced random environment which is ergodic under space-time shifts. We also obtain Gaussian…

Probability · Mathematics 2019-12-04 Jean-Dominique Deuschel , Xiaoqin Guo

In this paper we study the central limit theorem for additive functionals of stationary Markov chains with general state space by using a new idea involving conditioning with respect to both the past and future of the chain. Practically, we…

Probability · Mathematics 2020-05-19 Magda Peligrad

We establish central limit theorems for a large class of supercritical branching Markov processes in infinite dimension with spatially dependent and non-necessarily local branching mechanisms. This result relies on a fourth moment…

Probability · Mathematics 2025-01-31 Bertrand Cloez , Nicolás Zalduendo

In this paper, under mild assumptions, we derive a law of large numbers, a central limit theorem with an error estimate, an almost sure invariance principle and a variant of Chernoff bound in finite-state hidden Markov models. These limit…

Information Theory · Computer Science 2012-04-13 Guangyue Han

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked…

Statistics Theory · Mathematics 2015-06-18 Damien Passemier , Matthew R. Mckay , Yang Chen

Recently, Brandt et al. [STOC'16] proved a lower bound for the distributed Lov\'asz Local Lemma, which has been conjectured to be tight for sufficiently relaxed LLL criteria by Chang and Pettie [FOCS'17]. At the heart of their result lies a…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-27 Sebastian Brandt

We develop a quenched thermodynamic formalism for a wide class of random maps with non-uniform expansion, where no Markov structure, no uniformly bounded degree or the existence of some expanding dynamics is required. We prove that every…

Dynamical Systems · Mathematics 2024-04-19 Manuel Stadlbauer , Shintaro Suzuki , Paulo Varandas

Let $(\Omega, \A, \mu)$ be a Lebesgue space and $T$ an ergodic measure preserving automorphism on $\Omega$ with positive entropy. We show that there is a bounded and strictly stationary martingale difference sequence defined on $\Omega$…

Probability · Mathematics 2007-05-23 Mohamed El Machkouri , Dalibor Volny

In \cite{FTD1}, we proved the almost sure convergence of eigenvalues of the SYK model, which can be viewed as a type of \emph{law of large numbers} in probability theory; in \cite{FTD2}, we proved that the linear statistic of eigenvalues…

Mathematical Physics · Physics 2018-06-17 Renjie Feng , Gang Tian , Dongyi Wei
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