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This paper is concerned with the large deviation principle of the stochastic reaction-diffusion lattice systems defined on the N-dimensional integer set, where the nonlinear drift term is locally Lipschitz continuous with polynomial growth…

Dynamical Systems · Mathematics 2023-05-12 Bixiang Wang

This paper presents a new partial differential equation to build Brakke's motion, which is a weak notion of mean curvature flow. We call the equation a modified Allen-Cahn equation abbreviated to MAC. After that we introduce its benefit: An…

Analysis of PDEs · Mathematics 2022-08-04 Kazuhiro Horihata

Using a generalisation of the detailed balance for systems maintained out of equilibrium by contact with 2 reservoirs at unequal temperatures or at unequal densities, we recover the fluctuation theorem for the large deviation funtion of the…

Statistical Mechanics · Physics 2009-11-13 T. Bodineau , B. Derrida

We derive an annealed large deviation principle for the normalised local times of a continuous-time random walk among random conductances in a finite domain in $\Z^d$ in the spirit of Donsker-Varadhan \cite{DV75}. We work in the interesting…

Probability · Mathematics 2011-04-11 Wolfgang König , Michele Salvi , Tilman Wolff

Time-irreversible stochastic processes are frequently used in natural sciences to explain non-equilibrium phenomena and to design efficient stochastic algorithms. Our main goal in this thesis is to analyse their dynamics by means of large…

Probability · Mathematics 2021-09-21 Mikola C. Schlottke

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…

Probability · Mathematics 2020-12-29 Lea Popovic

This paper is mainly concerned with the large deviation principle of the fractional McKean-Vlasov stochastic reaction-diffusion equation defined on R^n with polynomial drift of any degree. We first prove the well-posedness of the underlying…

Probability · Mathematics 2024-06-18 Zhang Chen , Bixiang Wang

In this paper, we establish a large deviation principle for the solutions to the stochastic heat equations with logarithmic nonlinearity driven by Brownian motion, which is neither locally Lipschitz nor locally monotone. Nonlinear versions…

Probability · Mathematics 2022-07-07 Tianyi Pan , Shijie Shang , Tusheng Zhang

The Cahn-Hilliard equation with an externally-prescribed chaotic shear flow is studied in two and three dimensions. The main goal is to compare and contrast the phase separation in two and three dimensions, using high-resolution numerical…

Fluid Dynamics · Physics 2014-12-23 Lennon O'Naraigh , Selma Shun , Aurore Naso

We establish a sharp large deviation principle for renewal-reward processes, supposing that each renewal involves a broad-sense reward taking values in a real separable Banach space. In fact, we demonstrate a weak large deviation principle…

Probability · Mathematics 2023-04-24 Marco Zamparo

This paper is concerned with a fully nonlinear variant of the Allen-Cahn equation with strong irreversibility, where each solution is constrained to be non-decreasing in time. Main purposes of the paper are to prove the well-posedness,…

Analysis of PDEs · Mathematics 2018-01-30 Goro Akagi , Messoud Efendiev

In recent work [1] we uncovered intriguing connections between Otto's characterisation of diffusion as entropic gradient flow [16] on one hand and large-deviation principles describing the microscopic picture (Brownian motion) on the other.…

Analysis of PDEs · Mathematics 2014-03-05 Stefan Adams , Nicolas Dirr , Mark A. Peletier , Johannes Zimmer

This paper is concerned with the motion of a time dependent hypersurface that evolves by mean curvature flow with a a volume constraint. Phase field approximation of this motion leads to the well known nonlocal Allen--Cahn equation. Here we…

Numerical Analysis · Mathematics 2009-04-02 Elie Bretin , Morgan Brassel

The work concerns deviation estimates for multivalued McKean-Vlasov stochastic differential equations. First of all, we prove the large deviation principle for them by the weak convergence approach. Then the central limit theorem for them…

Probability · Mathematics 2022-08-10 Kun Fang , Huijie Qiao

We investigate the large deviation principle (LDP) of the stationary solutions of stochastic functional differential equations (SFDEs) with infinite delay under small random perturbation. First, we demonstrate the existence and uniqueness…

Probability · Mathematics 2026-05-18 Yong Liu , Bin Tang

This work is concerned with the large deviation principle for a family of slow-fast systems perturbed by infinite-dimensional mixed fractional Brownian motion with Hurst parameter $H\in(\frac12,1)$. We adopt the weak convergence method…

Probability · Mathematics 2025-09-16 Wenting Xu , Yong Xu , Xiaoyu Yang , Bin Pei

In this article, we consider slow-fast McKean-Vlasov stochastic differential equations driven by Brownian motions and fractional Brownian motions. We give a definition of the large deviation principle (LDP) on the product space related to…

Probability · Mathematics 2023-07-04 Hao Wu , Junhao Hu , Chenggui Yuan

We consider a stochastic partial differential equation with logarithmic (or negative power) nonlinearity, with one reflection at 0 and with a constraint of conservation of the space average. The equation, driven by the derivative in space…

Analysis of PDEs · Mathematics 2019-10-21 Ludovic Goudenège

This work focuses on multivalued stochastic differential equations with jumps. First, by employing the weak convergence approach, we establish the Freidlin-Wentzell uniform large deviation principle and the Dembo-Zeitouni uniform large…

Probability · Mathematics 2025-12-23 Huijie Qiao

Increasingly larger data sets of processes in space and time ask for statistical models and methods that can cope with such data. We show that the solution of a stochastic advection-diffusion partial differential equation provides a…

Methodology · Statistics 2016-02-18 Fabio Sigrist , Hans R. Künsch , Werner A. Stahel
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