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Main Authors: Hong, Wei, Liu, Wei, Yang, Luhan
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2402.18108
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author Hong, Wei
Liu, Wei
Yang, Luhan
author_facet Hong, Wei
Liu, Wei
Yang, Luhan
contents This paper is devoted to proving the small noise asymptotic behaviour, particularly large deviation principle, for multi-scale stochastic dynamical systems with fully local monotone coefficients driven by multiplicative noise. The main techniques are based on a combination of the weak convergence approach, the time discretization technique and the theory of pseudo-monotone operator. The main results derived in this paper have broad applicability to various multi-scale models, where the slow component could be such as stochastic porous medium equations, stochastic Cahn-Hilliard equations and stochastic 2D Liquid crystal equations.
format Preprint
id arxiv_https___arxiv_org_abs_2402_18108
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Large Deviation Principle for Multi-Scale Fully Local Monotone Stochastic Dynamical Systems with Multiplicative Noise
Hong, Wei
Liu, Wei
Yang, Luhan
Probability
This paper is devoted to proving the small noise asymptotic behaviour, particularly large deviation principle, for multi-scale stochastic dynamical systems with fully local monotone coefficients driven by multiplicative noise. The main techniques are based on a combination of the weak convergence approach, the time discretization technique and the theory of pseudo-monotone operator. The main results derived in this paper have broad applicability to various multi-scale models, where the slow component could be such as stochastic porous medium equations, stochastic Cahn-Hilliard equations and stochastic 2D Liquid crystal equations.
title Large Deviation Principle for Multi-Scale Fully Local Monotone Stochastic Dynamical Systems with Multiplicative Noise
topic Probability
url https://arxiv.org/abs/2402.18108