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In this paper, two novel classes of implicit exponential Runge-Kutta (ERK) methods are studied for solving highly oscillatory systems. First of all, we analyze the symplectic conditions of two kinds of exponential integrators, and present a…

Numerical Analysis · Mathematics 2023-12-05 Xianfa Hu , Wansheng Wang , Bin Wang , Yonglei Fang

In this manuscript, we propose efficient stochastic semi-explicit symplectic schemes tailored for nonseparable stochastic Hamiltonian systems (SHSs). These semi-explicit symplectic schemes are constructed by introducing augmented…

Numerical Analysis · Mathematics 2024-05-24 Jialin Hong , Baohui Hou , Liying Sun

Based on a variational principle with a stochastic forcing, we indicate that the stochastic Schr\"odinger equation in Stratonovich sense is an infinite-dimensional stochastic Hamiltonian system, whose phase flow preserves symplecticity. We…

Numerical Analysis · Mathematics 2016-05-05 Chuchu Chen , Jialin Hong

This paper aims to investigate the numerical approximation of a general second order parabolic stochastic partial differential equation(SPDE) driven by multiplicative and additive noise. Our main interest is on such SPDEs where the…

Numerical Analysis · Mathematics 2020-11-19 Jean Daniel Mukam , Antoine Tambue

In this paper we present a general procedure for designing higher strong order methods for It\^o stochastic differential equations on matrix Lie groups and illustrate this strategy with two novel schemes that have a strong convergence order…

Numerical Analysis · Mathematics 2021-02-09 Michelle Muniz , Matthias Ehrhardt , Michael Günther , Renate Winkler

This work gives the asymptotic error distribution of the stochastic Runge--Kutta (SRK) method of strong order $1$ applied to Stratonovich-type stochastic differential equations. For dealing with the implicitness introduced in the diffusion…

Numerical Analysis · Mathematics 2025-08-05 Diancong Jin

In this paper, we investigate the asymptotic error distributions of symplectic methods for stochastic Hamiltonian systems and further provide Hamiltonian-specific analysis that clarifies the superiority of symplectic methods. Our…

Numerical Analysis · Mathematics 2025-12-04 Chuchu Chen , Xinyu Chen , Jialin Hong , Yuqian Miao

A new class of third order Runge-Kutta methods for stochastic differential equations with additive noise is introduced. In contrast to Platen's method, which to the knowledge of the author has been up to now the only known third order…

Numerical Analysis · Mathematics 2010-09-29 Kristian Debrabant

Convenient, easy to implement stochastic integration methods are developed on the basis of abstract one-step deterministic order $p$ integration techniques. The abstraction as an arbitrary one step map allows the inspection of easy to…

Numerical Analysis · Mathematics 2025-10-15 J. Woodfield , A. Lobbe

Symplectic partitioned Runge--Kutta methods can be obtained from a variational formulation where all the terms in the discrete Lagrangian are treated with the same quadrature formula. We construct a family of symplectic methods allowing the…

Numerical Analysis · Mathematics 2019-09-25 Antonella Zanna

On the basis of the previous work by Tang \& Zhang (Appl. Math. Comput. 323, 2018, p. 204--219), in this paper we present a more effective way to construct high-order symplectic integrators for solving second order Hamiltonian equations.…

Numerical Analysis · Mathematics 2019-06-11 Wensheng Tang , Yajuan Sun , Jingjing Zhang

In this paper, we develop a higher order symmetric partitioned Runge-Kutta method for a coupled system of differential equations on Lie groups. We start with a discussion on partitioned Runge-Kutta methods on Lie groups of arbitrary order.…

High Energy Physics - Lattice · Physics 2011-09-15 Michèle Wandelt , Michael Günther , Francesco Knechtli , Michael Striebel

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 methods can preserve the Poisson structure, Casimir…

Numerical Analysis · Mathematics 2025-01-23 Liying Zhang , Fenglin Xue , Lijin Wang

In this paper, a systematic approach of constructing modified equations for weak stochastic symplectic methods of stochastic Hamiltonian systems is given via using the generating functions of the stochastic symplectic methods. This approach…

Numerical Analysis · Mathematics 2014-11-11 Lijin Wang , Jialin Hong

We introduce a family of stochastic optimization methods based on the Runge-Kutta-Chebyshev (RKC) schemes. The RKC methods are explicit methods originally designed for solving stiff ordinary differential equations by ensuring that their…

Optimization and Control · Mathematics 2022-02-01 Tony Stillfjord , Måns Williamson

We give a theoretical framework of stochastic non-canonical Hamiltonian systems as well as their modified symplectic structure which is named stochastic K-symplectic structure. The framework can be applied to the study of the…

Numerical Analysis · Mathematics 2017-11-10 Jialin Hong , Lihai Ji , Xu Wang , Jingjing Zhang

Stochastic Klein--Gordon--Schr\"odinger (KGS) equations are important mathematical models and describe the interaction between scalar nucleons and neutral scalar mesons in the stochastic environment. In this paper, we propose novel…

Numerical Analysis · Mathematics 2023-05-19 Jialin Hong , Baohui Hou , Liying Sun , Xiaojing Zhang

Stochastic Klein--Gordon--Schr\"odinger (KGS) equations are important mathematical models and describe the interaction between scalar nucleons and neutral scalar mesons in the stochastic environment. In this paper, we propose novel…

Numerical Analysis · Mathematics 2023-05-19 Jialin Hong , Baohui Hou , Liying Sun , Xiaojing Zhang

We show that symplectic Runge-Kutta methods provide effective symplectic integrators for Hamiltonian systems with index one constraints. These include the Hamiltonian description of variational problems subject to position and velocity…

Numerical Analysis · Mathematics 2014-02-28 Robert I McLachlan , Klas Modin , Olivier Verdier , Matt Wilkins

One- and multi-dimensional stochastic Maxwell equations with additive noise are considered in this paper. It is known that such system can be written in the multi-symplectic structure, and the stochastic energy increases linearly in time.…

Numerical Analysis · Mathematics 2022-05-04 Jiawei Sun , Chi-Wang Shu , Yulong Xing