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We establish the large deviation principle (LDP) for stochastic flows of interacting Brownian motions. In particular, we consider smoothly correlated flows, coalescing flows and Brownian motion stopped at a hitting moment.

概率论 · 数学 2009-07-21 A. A. Dorogovtsev , O. V. Ostapenko

The points of the closed range of a drift-free subordinator with no killing are used for separating into blocks the elements of a sample of size $n$ from the standard exponential distribution. This gives rise to a random composition of $n$.…

概率论 · 数学 2024-06-13 Alexander Iksanov , Wissem Jedidi

We study a class of graphon particle systems with time-varying random coefficients. In a graphon particle system, the interactions among particles are characterized by the coupled mean field terms through an underlying graphon and the…

系统与控制 · 电气工程与系统科学 2025-10-02 Yan Chen , Tao Li , Xiaofeng Zong

We study the convergence behavior of the stochastic heavy-ball method with a small stepsize. Under a change of time scale, we approximate the discrete method by a stochastic differential equation that models small random perturbations of a…

概率论 · 数学 2019-10-21 Wenqing Hu , Chris Junchi Li , Xiang Zhou

This work deals with first hitting time densities of Ito processes whose local drift can be modeled in terms of a solution to Burgers equation. In particular, we derive the densities of the first time that these processes reach a moving…

概率论 · 数学 2012-09-13 Gerardo Hernandez-del-Valle

We study the extremes of variable speed branching Brownian motion (BBM) where the time-dependent "speed functions", which describe the time-inhomogeneous variance, converge to the identity function. We consider general speed functions lying…

概率论 · 数学 2025-03-03 Alexander Alban , Anton Bovier , Annabell Gros , Lisa Hartung

Let (B^{(1)}_t ;B^{(2)}_t ;B^{(3)}_t + \mu t) be a three-dimensional Brownian motion with drift \mu, starting at the origin. Then X_t = ||(B^{(1)}_t ;B^{(2)}_t ;B^{(3)}_t +\mu t)||, its distance from the starting point, is a diffusion with…

概率论 · 数学 2015-01-15 Andrzej Pyć , Grzegorz Serafin , Tomasz Żak

Consider the $n$th iterated Brownian motion $I^{(n)}=B_n \circ\cdots \circ B_1$. Curien and Konstantopoulos proved that for any distinct numbers $t_i\neq 0$, $(I^{(n)}(t_1),\dots,I^{(n)}(t_k))$ converges in distribution to a limit $I[k]$…

概率论 · 数学 2015-04-27 Jérôme Casse , Jean-François Marckert

We investigate a functional obtained by summing the squared differences of the integral of an Ito process over disjoint intervals. The limit of this sum is shown to converge in probability to two thirds the quadratic variation of the…

概率论 · 数学 2013-08-14 John F. A. Fletcher

This paper focuses on systems of nonlinear second-order stochastic differential equations with multi-scales. The motivation for our study stems from mathematical physics and statistical mechanics, for examples, Langevin dynamics and…

概率论 · 数学 2024-04-08 Nhu N. Nguyen , George Yin

We consider the branching random walk drifting to $-\infty$ and we investigate large deviations-type estimates for the first passage time. We prove the corresponding law of large numbers and the central limit theorem.

概率论 · 数学 2017-09-14 Dariusz Buraczewski , Mariusz Maslanka

One century after Einstein's work, Brownian Motion still remains both a fundamental open issue and a continous source of inspiration for many areas of natural sciences. We first present a discussion about stochastic and deterministic…

混沌动力学 · 物理学 2009-11-10 Fabio Cecconi , Massimo Cencini , Massimo Falcioni , Angelo Vulpiani

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…

概率论 · 数学 2007-05-23 R. van der Hofstad , F. den Hollander , W. Koenig

We obtain large deviation results for a two time-scale model of jump-diffusion processes. The processes on the two time scales are fully inter-dependent, the slow process has small perturbative noise and the fast process is ergodic. Our…

概率论 · 数学 2016-09-19 Rohini Kumar , Lea Popovic

In this paper, we study the large deviation principle of invariant measures of stochastic reaction-diffusion lattice systems driven by multiplicative noise. We first show that any limit of a sequence of invariant measures of the stochastic…

概率论 · 数学 2024-05-07 Bixiang Wang

For Markov processes evolving on multiple time-scales a combination of large component scalings and averaging of rapid fluctuations can lead to useful limits for model approximation. A general approach to proving a law of large numbers to a…

概率论 · 数学 2020-12-29 Lea Popovic

We consider a family of continuous processes $\{X^\varepsilon\}_{\varepsilon>0}$ which are measurable with respect to a white noise measure, take values in the space of continuous functions $C([0,1]^d:\mathbb{R})$, and have the Wiener chaos…

概率论 · 数学 2023-02-01 Alexandre Pannier

We study a Schilder-type large deviation principle for sticky-reflected Brownian motion with boundary diffusion, both at the static and sample path level in the short-time limit. A sharp transition for the rate function occurs, depending on…

偏微分方程分析 · 数学 2025-01-22 Jean-Baptiste Casteras , Leonard Monsaingeon , Luca Nenna

In this work, we characterize cluster-invariant point processes for critical branching spatial processes on R d for all large enough d when the motion law is $\alpha$-stable or has a finite discrete range. More precisely, when the motion is…

概率论 · 数学 2022-06-17 Valentin Rapenne

Let $X$ be the branching particle diffusion corresponding to the operator $Lu+\beta (u^{2}-u)$ on $D\subseteq \mathbb{R}^{d}$ (where $\beta \geq 0$ and $\beta\not\equiv 0$). Let $\lambda_{c}$ denote the generalized principal eigenvalue for…

概率论 · 数学 2007-09-04 Janos Englander , Simon C. Harris , Andreas E. Kyprianou