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A stochastic Burgers equation from a class of microscopic interactions

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Detalhes bibliográficos
Resumo:We consider a class of nearest-neighbor weakly asymmetric mass conservative particle systems evolving on $\mathbb{Z}$, which includes zero-range and types of exclusion processes, starting from a perturbation of a stationary state. When the weak asymmetry is of order $O(n^\gamma)$ for $1/2<\gamma\leq 1$, we show that the scaling limit of the fluctuation field, as seen across process characteristics, is a generalized Ornstein-Uhlenbeck process. However, at the critical weak asymmetry when $\gamma = 1/2$, we show that all limit points solve a martingale problem which may be interpreted in terms of a stochastic Burgers equation derived from taking the gradient of the KPZ equation. The proofs make use of a sharp `Boltzmann-Gibbs' estimate which improves on earlier bounds.
Autores principais:Gonçalves, Patrícia
Outros Autores:Jara, Milton; Sethuraman, Sunder
Assunto:KPZ equation Burgers Weakly asymmetric Zero-range Kinetically constrained Equilibrium fluctuations Speed-change Fluctuations weakly asymetric
Ano:2015
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:We consider a class of nearest-neighbor weakly asymmetric mass conservative particle systems evolving on $\mathbb{Z}$, which includes zero-range and types of exclusion processes, starting from a perturbation of a stationary state. When the weak asymmetry is of order $O(n^\gamma)$ for $1/2<\gamma\leq 1$, we show that the scaling limit of the fluctuation field, as seen across process characteristics, is a generalized Ornstein-Uhlenbeck process. However, at the critical weak asymmetry when $\gamma = 1/2$, we show that all limit points solve a martingale problem which may be interpreted in terms of a stochastic Burgers equation derived from taking the gradient of the KPZ equation. The proofs make use of a sharp `Boltzmann-Gibbs' estimate which improves on earlier bounds.