activity
20192024
most citedA symplectic discontinuous Galerkin full discretization for stochastic Maxwell equations

3 citations · 6 across the 10 of their papers we have counts for

collaborators
Showing math.NAShow all

8 papers · 1 filter

math.NA2022

An adaptive time-stepping fully discrete scheme for stochastic NLS equation: Strong convergence and numerical asymptotics

Chuchu Chen, Tonghe Dang, Jialin Hong

In this paper, we propose and analyze an adaptive time-stepping fully discrete scheme which possesses the optimal strong convergence order for the stochastic nonlinear Schrödinger…

math.NA2022

Ergodic numerical approximations for stochastic Maxwell equations

Chuchu Chen, Jialin Hong, Lihai Ji +1

In this paper, we propose a novel kind of numerical approximations to inherit the ergodicity of stochastic Maxwell equations. The key to proving the ergodicity lies in the uniform…

math.NA2021

Large deviations principles of sample paths and invariant measures of numerical methods for parabolic SPDEs

Chuchu Chen, Ziheng Chen, Jialin Hong +1

For parabolic stochastic partial differential equations (SPDEs), we show that the numerical methods, including the spatial spectral Galerkin method and further the full discretizat…

math.NA2021

Weak intermittency and second moment bound of a fully discrete scheme for stochastic heat equation

Chuchu Chen, Tonghe Dang, Jialin Hong

In this paper, we first prove the weak intermittency, and in particular the sharp exponential order of the second moment of the exact solution of the stochastic heat equati…

math.NA2021

A new efficient operator splitting method for stochastic Maxwell equations

Chuchu Chen, Jialin Hong, Lihai Ji

This paper proposes and analyzes a new operator splitting method for stochastic Maxwell equations driven by additive noise, which not only decomposes the original multi-dimensional…

math.NA20203 cited

A symplectic discontinuous Galerkin full discretization for stochastic Maxwell equations

Chuchu Chen

This paper proposes a fully discrete method called the symplectic dG full discretization for stochastic Maxwell equations driven by additive noises, based on a stochastic symplecti…