Backward error analysis for conjugate symplectic methods

Author:

McLachlan Robert I1,Offen Christian2

Affiliation:

1. Massey University, Private Bag 11 222, Palmerston North 4442, New Zealand

2. Paderborn University, Warburger Str. 100, 33098 Paderborn, Germany

Abstract

<abstract><p>The numerical solution of an ordinary differential equation can be interpreted as the exact solution of a nearby modified equation. Investigating the behaviour of numerical solutions by analysing the modified equation is known as backward error analysis. If the original and modified equation share structural properties, then the exact and approximate solution share geometric features such as the existence of conserved quantities. Conjugate symplectic methods preserve a modified symplectic form and a modified Hamiltonian when applied to a Hamiltonian system. We show how a blended version of variational and symplectic techniques can be used to compute modified symplectic and Hamiltonian structures. In contrast to other approaches, our backward error analysis method does not rely on an ansatz but computes the structures systematically, provided that a variational formulation of the method is known. The technique is illustrated on the example of symmetric linear multistep methods with matrix coefficients.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Control and Optimization,Geometry and Topology,Mechanics of Materials

Reference16 articles.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Learning of discrete models of variational PDEs from data;Chaos: An Interdisciplinary Journal of Nonlinear Science;2024-01-01

2. Variational learning of Euler–Lagrange dynamics from data;Journal of Computational and Applied Mathematics;2023-03

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