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Hamiltonian systems are one of the most important class of dynamical systems with a geometric structure called symplecticity and the numerical algorithms which can preserve such geometric structure are of interest. In this article we study…

Numerical Analysis · Mathematics 2015-10-16 Wensheng Tang , Guangming Lang , Xuqiong Luo

We consider Hamiltonian systems driven by multi-dimensional Gaussian processes in rough path sense, which include fractional Brownian motions with Hurst parameter $H\in(1/4,1/2]$. We indicate that the phase flow preserves the symplectic…

Numerical Analysis · Mathematics 2018-03-20 Jialin Hong , Chuying Huang , Xu Wang

We propose a family of integrators, Flow-Composed Implicit Runge-Kutta (FCIRK) methods, for perturbations of nonlinear ordinary differential equations, consisting of the composition of flows of the unperturbed part alternated with one step…

Numerical Analysis · Mathematics 2017-11-17 Mikel Antoñana , Joseba Makazaga , Ander Murua

Generalized Additive Runge-Kutta schemes have shown to be a suitable tool for solving ordinary differential equations with additively partitioned right-hand sides. This work develops symplectic GARK schemes for additively partitioned…

Numerical Analysis · Mathematics 2023-12-14 Michael Günther , Adrian Sandu , Kevin Schäfers , Antonella Zanna

The generalized additive Runge-Kutta (GARK) framework provides a powerful approach for solving additively partitioned ordinary differential equations. This work combines the ideas of symplectic GARK schemes and multirate GARK schemes to…

Numerical Analysis · Mathematics 2023-12-15 Kevin Schäfers , Michael Günther , Adrian Sandu

The phase space of a Hamiltonian system is symplectic. However, the post-Newtonian Hamiltonian formulation of spinning compact binaries in existing publications does not have this property, when position, momentum and spin variables $[X, P,…

General Relativity and Quantum Cosmology · Physics 2010-05-12 Xin Wu , Yi Xie

Based on reasonable testing model problems, we study the preservation by symplectic Runge-Kutta method (SRK) and symplectic partitioned Runge-Kutta method (SPRK) of structures for fixed points of linear Hamiltonian systems. The…

Numerical Analysis · Mathematics 2008-02-18 Xiaohua Ding , Hongyu Liu , Zaijiu Shang , Geng Sun , Lingshu Wang

We study symplectic numerical integration of mechanical systems with a Hamiltonian specified in non-canonical coordinates and its application to guiding-center motion of charged plasma particles in magnetic confinement devices. The…

Computational Physics · Physics 2020-01-29 Christopher G. Albert , Sergei V. Kasilov , Winfried Kernbichler

Symmetric method and symplectic method are classical notions in the theory of Runge-Kutta methods. They can generate numerical flows that respectively preserve the symmetry and symplecticity of the continuous flows in the phase space.…

Numerical Analysis · Mathematics 2018-08-17 Geng Sun , Siqing Gan , Hongyu Liu , Zaijiu Shang

We are concerned with the efficient implementation of symplectic implicit Runge-Kutta (IRK) methods applied to systems of (non-necessarily Hamiltonian) ordinary differential equations by means of Newton-like iterations. We pay particular…

Numerical Analysis · Mathematics 2017-03-23 Mikel Antoñana , Joseba Makazaga , Ander Murua

We propose efficient numerical methods for nonseparable non-canonical Hamiltonian systems which are explicit, K-symplectic in the extended phase space with long time energy conservation properties. They are based on extending the original…

Numerical Analysis · Mathematics 2023-03-01 Beibei Zhu , Lun Ji , Aiqing Zhu , Yifa Tang

We propose a new method to prove the partitioned Runge--Kutta methods with symplectic conditions for determinate and stochastic Hamiltonian systems are symplectic. We utilize Gr\"obner basis technology which is the one of symbolic…

Numerical Analysis · Mathematics 2025-09-16 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

This paper analyses the long-time behaviour of one-stage symplectic or symmetric extended Runge--Kutta--Nystr\"{o}m (ERKN) methods when applied to nonlinear wave equations. It is shown that energy, momentum, and all harmonic actions are…

Numerical Analysis · Mathematics 2018-10-04 Bin Wang , Xinyuan Wu

This paper studies diagonal implicit symplectic extended Runge--Kutta--Nystr\"{o}m (ERKN) methods for solving the oscillatory Hamiltonian system $H(q,p)=\dfrac{1}{2}p^{T}p+\dfrac{1}{2}q^{T}Mq+U(q)$. Based on symplectic conditions and order…

Numerical Analysis · Mathematics 2017-12-04 Mingxue Shi , Hao Zhang , Bin Wang

A novel symplectic integrator for Hamiltonian equations on $S_2^n \times T^{\ast} \RR^m$ is developed and studied. Partitioned Runge--Kutta methods for Hamiltonian systems on products of Hamiltionian manifolds are studied, specifically,…

Numerical Analysis · Mathematics 2018-09-18 Geir Bogfjellmo

In this paper, we study symplectic integration of canonical Hamiltonian systems with Jacobi polynomials. The relevant theoretical results of continuous-stage Runge-Kutta methods are revisited firstly and then symplectic methods with Jacobi…

Numerical Analysis · Mathematics 2025-07-23 Wensheng Tang

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

We design a novel, exactly energy-conserving implicit non-symplectic integration method for an eight-dimensional Hamiltonian system with four degrees of freedom. In our algorithm, each partial derivative of the Hamiltonian with respect to…

General Relativity and Quantum Cosmology · Physics 2019-12-30 Shiyang Hu , Xin Wu , Guoqing Huang , Enwei Liang

Runge-Kutta methods are affine equivariant: applying a method before or after an affine change of variables yields the same numerical trajectory. However, for some applications, one would like to perform numerical integration after a…

Numerical Analysis · Mathematics 2026-03-17 Ari Stern , Milo Viviani
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