5 papers
Two operator splitting methods for three-dimensional stochastic Maxwell equations with multiplicative noise
Liying Zhang, Xinyue Kang, Lihai Ji
In this paper, we develop two energy-preserving splitting methods for solving three-dimensional stochastic Maxwell equations driven by multiplicative noise. We use operator splitti…
Stochastic positivity-preserving symplectic splitting methods for stochastic Lotka--Volterra predator-prey model
Liying Zhang, Xinyue Kang, Lihai Ji
In this paper, we present two stochastic positive-preserving symplectic methods for the stochastic Lotka-Volterra predator-prey model driven by a multiplicative noise. To inherit t…
Wiener chaos expansion for stochastic Maxwell equations driven by Wiener process
Lihai Ji, Kuan Xue, Liying Zhang
A novel and efficient algorithm based on the Wiener chaos expansion is proposed for the stochastic Maxwell equations driven by Wiener process. The proposed algorithm can reduce the…
Optimal Estimation and Uncertainty Quantification for Stochastic Inverse Problems via Variational Bayesian Methods
Ruibiao Song, Liying Zhang
The Bayesian inversion method demonstrates significant potential for solving inverse problems, enabling both point estimation and uncertainty quantification (UQ). However, Bayesian…
Structure-Preserving Implicit Runge-Kutta Methods for Stochastic Poisson Systems with Multiple Noises
Liying Zhang, Fenglin Xue, Lijin Wang
In this paper, we propose the diagonal implicit Runge-Kutta methods and transformed Runge-Kutta methods for stochastic Poisson systems with multiple noises. We prove that the first…