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Related papers: Short time large deviations of the KPZ equation

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In this note, we prove a sharp large derivation principle (LDP) for the cubic nonlinear Schr\"odinger equation with Gaussian random initial data in Fourier Lebesgue spaces. As a consequence, we improve the exponential decay condition in…

Analysis of PDEs · Mathematics 2025-12-09 Rui Liang , Yuzhao Wang

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…

Probability · Mathematics 2024-05-07 Bixiang Wang

We establish a large deviation principle for the Kardar-Parisi-Zhang (KPZ) equation, providing precise control over the left tail of the height distribution for narrow wedge initial condition. Our analysis exploits an exact connection…

Statistical Mechanics · Physics 2018-08-15 Ivan Corwin , Promit Ghosal , Alexandre Krajenbrink , Pierre Le Doussal , Li-Cheng Tsai

This paper establishs the large deviation principle (LDP) for multiple averages on $\mathbb{N}^d$. We extend the previous work of [Carinci et al., Indag. Math. 2012] to multidimensional lattice $\mathbb{N}^d$ for $d\geq 2$. The same…

Probability · Mathematics 2021-06-21 Jung-Chao Ban , Wen-Guei Hu , Guan-Yu Lai

In this paper, we first provide a criterion on uniform large deviation principles (ULDP) of stochastic differential equations under Lyapunov conditions on the coefficients, which can be applied to stochastic systems with coefficients of…

Probability · Mathematics 2024-02-27 Jifa Jiang , Jian Wang , Jianliang Zhai , Tusheng Zhang

We study in this series of articles the Kardar-Parisi-Zhang (KPZ) equation $$ \partial_t h(t,x)=\nu\Delta h(t,x)+\lambda V(|\nabla h(t,x)|) +\sqrt{D}\, \eta(t,x), \qquad x\in{\mathbb{R}}^d $$ in $d\ge 1$ dimensions. The forcing term $\eta$…

Analysis of PDEs · Mathematics 2015-10-27 Jeremie Unterberger

Large deviations principles characterize the exponential decay rates of the probabilities of rare events. Cerrai and Rockner [13] proved that systems of stochastic reaction-diffusion equations satisfy a large deviations principle that is…

Probability · Mathematics 2021-08-11 Michael Salins

We establish a large deviation principle for the solutions of a class of stochastic partial differential equations with non-Lipschitz continuous coefficients. As an application, the large deviation principle is derived for super-Brownian…

Probability · Mathematics 2012-05-11 Parisa Fatheddin , Jie Xiong

We approximate the white-noise driven stochastic heat equation by replacing the fractional Laplacian by the generator of a discrete time random walk on the one dimensional lattice, and approximating white noise by a collection of i.i.d.…

Probability · Mathematics 2017-06-20 Mathew Joseph

In this article we review the ideas in Tsai (2018) toward proving the one-point, lower-tail large deviation principle for the Kardar--Parisi--Zhang equation.

Probability · Mathematics 2022-06-14 Li-Cheng Tsai

The present paper focuses on the stochastic nonlinear Schrodinger equation with polynomial nonlinearity, and a zero-order (no derivatives involved) linear damping. Here, the random forcing term appears as a mix of a nonlinear noise in the…

Probability · Mathematics 2026-03-31 Sandip Roy , Debopriya Mukherjee , Manil Thankamani Mohan

We deal with a class of abstract nonlinear stochastic models, which covers many 2D hydrodynamical models including 2D Navier-Stokes equations, 2D MHD models and 2D magnetic B\'enard problem and also some shell models of turbulence. We first…

Probability · Mathematics 2011-12-15 Igor Chueshov , Annie Millet

We establish large deviation principles (LDPs) for empirical measures associated with a sequence of Gibbs distributions on $n$-particle configurations, each of which is defined in terms of an inverse temperature $% \beta_n$ and an energy…

Probability · Mathematics 2020-01-07 Paul Dupuis , Vaios Laschos , Kavita Ramanan

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

This article generalizes the small noise cutoff phenomenon to the strong solutions of the stochastic heat equation and the damped stochastic wave equation over a bounded domain subject to additive and multiplicative Wiener and L\'evy noises…

Probability · Mathematics 2023-05-08 G. Barrera , M. A. Högele , J. C. Pardo

We establish the existence and uniqueness of local strong pathwise solutions to the stochastic Boussinesq equations with partial diffusion term forced by multiplicative noise on the torus in $\mathbb{R}^{d},d=2,3$. The solution is strong in…

Analysis of PDEs · Mathematics 2020-09-25 Zhaoyang Qiu , Yanbin Tang

The Kardar-Parisi-Zhang (KPZ) equation is a stochastic partial differential equation which is ill-posed because the nonlinearity is marginally defined with respect to the roughness of the forcing noise. However, its Cole-Hopf solution,…

Probability · Mathematics 2014-07-29 Tadahisa Funaki , Jeremy Quastel

We consider a system of stochastic interacting particles in $\mathbb{R}^d$ and we describe large deviations asymptotics in a joint mean-field and small-noise limit. Precisely, a large deviations principle (LDP) is established for the…

Probability · Mathematics 2020-11-17 Carlo Orrieri

For a class of non-linear stochastic heat equations driven by $\alpha$-stable white noises for $\alpha\in(1,2)$ with Lipschitz coefficients, we first show the existence and pathwise uniqueness of $L^p$-valued c\`{a}dl\`{a}g solutions to…

Probability · Mathematics 2024-04-02 Yongjin Wang , Chengxin Yan , Xiaowen Zhou

Kardar-Parisi-Zhang (KPZ) equation is a quasilinear stochastic partial differential equation(SPDE) driven by a space-time white noise. In recent years there have been several works directed towards giving a rigorous meaning to a solution of…

Probability · Mathematics 2014-06-24 Sergio A. Almada Monter , Amarjit Budhiraja
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