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We derive the following property of the "true self-repelling motion", a continuous real-valued self-interacting process (X_t, t \ge 0) introduced by Balint Toth and Wendelin Werner. Conditionally on its occupation time measure at time one…

Probability · Mathematics 2014-01-27 Laure Dumaz

The true self-repelling motion is a continuous-time random process which was introduced by T\'oth and Werner in 1998 to be a limit for the "true" self-avoiding random walk defined by T\'oth in 1995. The construction of the true…

Probability · Mathematics 2026-02-26 Laure Marêché

We combine hydrodynamic and modulated energy techniques to study the large deviations of systems of particles with pairwise singular repulsive interactions and additive noise. Specifically, we examine periodic Riesz interactions indexed by…

Probability · Mathematics 2024-08-20 Elias Hess-Childs

We study the large deviation estimates for the short time asymptotic behavior of a strongly degenerate diffusion process. Assuming a nilpotent structure of the Lie algebra generated by the driving vector fields, we obtain a graded large…

Probability · Mathematics 2019-01-30 Gérard Ben Arous , Jing Wang

We prove a Large Deviations Principle (LDP) for systems of diffusions (particles) interacting through their ranks, when the number of particles tends to infinity. We show that the limiting particle density is given by the unique solution of…

Probability · Mathematics 2017-04-05 Amir Dembo , Mykhaylo Shkolnikov , S. R. Srinivasa Varadhan , Ofer Zeitouni

In this paper we prove a large deviation principle for the empirical drift of a one-dimensional Brownian motion with self-repellence called the Edwards model. Our results extend earlier work in which a law of large numbers, respectively, a…

Probability · Mathematics 2007-05-23 R. van der Hofstad , F. den Hollander , W. Koenig

We present large deviations estimates in the supremum norm for a system of independent random walks superposed with a birth-and-death dynamics evolving on the discrete torus with $N$ sites. The scaling limit considered is the so-called…

Probability · Mathematics 2021-02-26 Tertuliano Franco , Luana A. Gurgel , Bernardo N. B. de Lima

We investigate large deviations for the empirical measure of the position and momentum of a particle traveling in a box with hot walls. The particle travels with uniform speed from left to right, until it hits the right boundary. Then it is…

Probability · Mathematics 2011-03-16 Raphael Lefevere , Mauro Mariani , Lorenzo Zambotti

We consider large deviations of empirical measures of diffusion processes. In a first part, we present conditions to obtain a large deviations principle (LDP) for a precise class of unbounded functions. This provides an analogue to the…

Probability · Mathematics 2020-09-23 Grégoire Ferré , Gabriel Stoltz

We consider a collection of weakly interacting diffusion processes moving in a two-scale locally periodic environment. We study the large deviations principle of the empirical distribution of the particles' positions in the combined limit…

Probability · Mathematics 2022-11-03 Zachary Bezemek , Konstantinos Spiliopoulos

In this paper we present a new and flexible method to show that, in one dimension, various self-repellent random walks converge to self-repellent Brownian motion in the limit of weak interaction after appropriate space-time scaling. Our…

Probability · Mathematics 2007-05-23 R. van der Hofstad , F. den Hollander , W. Koenig

Self-interacting diffusions are processes living on a compact Riemannian manifold defined by a stochastic differential equation with a drift term depending on the past empirical measure of the process. The asymptotics of this measure is…

Probability · Mathematics 2009-08-03 Michel Benaim , Olivier Raimond

In this paper we explore maximal deviations of large random structures from their typical behavior. We introduce a model for a high-dimensional random graph process and ask analogous questions to those of Vapnik and Chervonenkis for…

Large deviation principles are established for the two-parameter Poisson-Dirichlet distribution and two-parameter Dirichlet process when parameter $\theta$ approaches infinity. The motivation for these results is to understand the…

Probability · Mathematics 2007-05-23 Shui Feng

We consider a jump-diffusion process on a bounded domain with reflection at the boundary, and establish long-term results for a general additive process of its path. This includes the long-term behaviour of its occupation time in the…

Probability · Mathematics 2022-07-29 Lea Popovic , Giovanni Zoroddu

Large-deviations theory deals with tails of probability distributions and the rare events of random processes, for example spreading packets of particles. Mathematically, it concerns the exponential fall-of of the density of thin-tailed…

Statistical Mechanics · Physics 2017-07-04 Erez Aghion , David A. Kessler , Eli Barkai

We theoretically study the transport properties of self-propelled particles on complex structures, such as motor proteins on filament networks. A general master equation formalism is developed to investigate the persistent motion of…

Soft Condensed Matter · Physics 2014-09-19 M. Reza Shaebani , Zeinab Sadjadi , Igor M. Sokolov , Heiko Rieger , Ludger Santen

This paper deals with the large deviations behavior of a stochastic process called thinned Levy process. This process appeared recently as a stochastic-process limit in the context of critical inhomogeneous random graphs. The process has a…

Probability · Mathematics 2014-04-08 Elie Aidekon , Remco van der Hofstad , Sandra Kliem , Johan S. H. van Leeuwaarden

Large deviation theory quantifies the occurence of events that deviate from the average behavior of a system. Such events arise from non-typical trajectories of the dynamics. In this note we derive the time evolution of these rare…

Statistical Mechanics · Physics 2012-12-11 David Andrieux

This paper investigates the large deviation problem in the sample path space of the nearest-neighbor random walks on regular trees. We establish the sample path large deviation principle for the law of the distance from a nearest random…

Probability · Mathematics 2025-05-07 Jie Jiang , Shuwen Lai
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