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We investigate the rate functions that emerge in our previous works towards large deviation principle for the matrix liberation process driven by the unitary Brownian motion as well as the unitary Brownian motion itself. Our approach is…

Probability · Mathematics 2026-03-27 Yoshimichi Ueda

Let O the basin of attraction of the unique stable equilibrium of a dynamical system, which is the law of large numbers limit of a Poissonian SDE. We consider the law of the exit point from O of that Poissonian SDE. We adapt the approach of…

Probability · Mathematics 2020-03-09 Etienne Pardoux , Brice Samegni-Kepgnou

In this paper we derive a Large Deviation Principle (LDP) for inhomogeneous U/V-statistics of a general order. Using this, we derive a LDP for two types of statistics: random multilinear forms, and number of monochromatic copies of a…

Probability · Mathematics 2026-04-01 Sohom Bhattacharya , Nabarun Deb , Sumit Mukherjee

We prove that the occupation measures of Brownian motions conditioned to have large intersections converge weakly, up to spatial shifts, to the measure whose density is the square of an optimizer of the Gagliardo-Nirenberg inequality. We do…

Probability · Mathematics 2026-05-08 Jiyun Park

Birth-death processes form a natural class where ideas and results on large deviations can be tested. In this paper, we derive a large deviation principle under the assumption that the rate of a jump down (death) is growing asymptotically…

Probability · Mathematics 2023-08-21 N. D. Vvedenskaya , A. V. Logachov , Y. M. Suhov , A. A. Yambartsev

We derive an annealed large deviation principle (LDP) for the normalised and rescaled local times of a continuous-time random walk among random conductances (RWRC) in a time-dependent, growing box in $\Z^d$. We work in the interesting case…

Probability · Mathematics 2013-08-22 Wolfgang König , Tilman Wolff

In this article, we develop a framework to study the large deviation principle for matrix models and their quantized versions, by tilting the measures using the limits of spherical integrals obtained in [46,47]. As examples, we obtain 1. a…

Probability · Mathematics 2023-04-25 Serban Belinschi , Alice Guionnet , Jiaoyang Huang

This paper deals with rare events in a general {interacting gas} at high temperature, by means of Large Deviations Principles. The main result is an LDP for the tagged empirical field, which features the competition of an energy term and an…

Probability · Mathematics 2025-06-17 David Padilla-Garza

We study the precise large deviation probabilities for the sizes of intermediate level sets in branching Brownian motion (BBM). Our conclusions improve a result of A\"{i}dekon, Hu and Shi in [J. Math. Sci. \textbf{238}(2019)]. Additionally,…

Probability · Mathematics 2025-05-07 Xinxin Chen , Heng Ma

In this paper, we provide a rigorous derivation of asymptotic formula for the largest eigenvalues using the convergence estimation of the eigenvalues of a sequence of self-adjoint compact operators of perturbations resulting from the…

Analysis of PDEs · Mathematics 2016-12-02 M. Gozzi , A. Khelifi

We derive a large deviation principle for the density profile of occupation times of random interlacements at a fixed level in a large box of Z^d, with d bigger or equal to 3. As an application, we analyze the asymptotic behavior of the…

Probability · Mathematics 2015-02-09 Xinyi Li , Alain-Sol Sznitman

Brownian motion is the only random process which is Gaussian, stationary and Markovian. Dropping the Markovian property, i.e. allowing for memory, one obtains a class of processes called fractional Brownian motion, indexed by the Hurst…

Statistical Mechanics · Physics 2016-07-27 Mathieu Delorme , Kay Jörg Wiese

We establish universality for the largest singular values of products of random matrices with right unitarily invariant distributions, in a regime where the number of matrix factors and size of the matrices tend to infinity simultaneously.…

Probability · Mathematics 2022-01-31 Andrew Ahn

The goal of this paper is to go further in the analysis of the behavior of the number of descents in a random permutation. Via two different approaches relying on a suitable martingale decomposition or on the Irwin-Hall distribution, we…

Probability · Mathematics 2024-11-20 Bernard Bercu , Michel Bonnefont , Adrien Richou

We show that the uniform norm of generalized grey Brownian motion over the unit interval has an analytic density, excluding the special case of fractional Brownian motion. Our main result is an asymptotic expansion for the small ball…

Probability · Mathematics 2023-01-13 Stefan Gerhold

Generalized Large deviation principles was developed for Colombeau-Ito SDE with a random coefficients. We is significantly expand the classical theory of large deviations for randomly perturbed dynamical systems developed by Freidlin and…

Mathematical Physics · Physics 2024-06-03 Jaykov Foukzon

We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the small noise limit when, possibly, all the jump rates vanish uniformly, but slowly enough, in a region of the state space. We further discuss the…

Probability · Mathematics 2021-02-26 Andrea Agazzi , Luisa Andreis , Robert I. A. Patterson , D. R. Michiel Renger

For $0\le \alpha <1$ and $\beta>2$, we consider a linear mod 1 transformation on a unit interval; $x\mapsto\beta x+\alpha$ (${\rm mod}\ 1$), and prove that it satisfies the level-2 large deviation principle with the unique measure of…

Dynamical Systems · Mathematics 2020-03-18 Yong Moo Chung ad Kenichiro Yamamoto

Consider the stochastic differential equation in $\rr^d$ dX^{\e}_t&=b(X^{\e}_t)dt+\sqrt{\e}\sigma(X^\e_t)dB_t X^{\e}_0&=x_0,\quad x_0\in\rr^d$ where $b:\rr^d\to\rr^d$ is $C^1$ such that $<x,b(x)> \leq C(1+|x|^2)$, $\sigma:\rr^d\to…

Probability · Mathematics 2026-04-14 Yutao ma , Ran Wang , Liming Wu

The incidence of rare events in fast-slow systems is investigated via analysis of the large deviation principle (LDP) that characterizes the likelihood and pathway of large fluctuations of the slow variables away from their mean behavior --…

Statistical Mechanics · Physics 2016-02-17 Freddy Bouchet , Tobias Grafke , Tomás Tangarife , Eric Vanden-Eijnden