Derivative-free discrete gradient methods

Fuente: arXiv
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Hauptverfasser: Myhr, Håkon Noren, Eidnes, Sølve
Format: Preprint
Veröffentlicht: 2026
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author Myhr, Håkon Noren
Eidnes, Sølve
author_facet Myhr, Håkon Noren
Eidnes, Sølve
contents Discrete gradient methods are a class of numerical integrators producing solutions with exact preservation of first integrals of ordinary differential equations. In this paper, we apply order theory combined with the symmetrized Itoh--Abe discrete gradient and finite differences to construct an integral-preserving fourth-order method that is derivative-free. The numerical scheme is implicit and a convergence result for Newton's iterations is provided, taking into account how the error due to the finite difference approximations affects the convergence rate. Numerical experiments verify the order and show that the derivative-free method is significantly faster than obtaining derivatives by automatic differentiation. Finally, an experiment using topographic data as the potential function of a Hamiltonian oscillator demonstrates how this method allows the simulation of discrete-time dynamics from a Hamiltonian that is a combination of data and analytical expressions.
format Preprint
id arxiv_https___arxiv_org_abs_2601_07479
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Derivative-free discrete gradient methods
Myhr, Håkon Noren
Eidnes, Sølve
Numerical Analysis
Primary 65L99, Secondary 65L12
Discrete gradient methods are a class of numerical integrators producing solutions with exact preservation of first integrals of ordinary differential equations. In this paper, we apply order theory combined with the symmetrized Itoh--Abe discrete gradient and finite differences to construct an integral-preserving fourth-order method that is derivative-free. The numerical scheme is implicit and a convergence result for Newton's iterations is provided, taking into account how the error due to the finite difference approximations affects the convergence rate. Numerical experiments verify the order and show that the derivative-free method is significantly faster than obtaining derivatives by automatic differentiation. Finally, an experiment using topographic data as the potential function of a Hamiltonian oscillator demonstrates how this method allows the simulation of discrete-time dynamics from a Hamiltonian that is a combination of data and analytical expressions.
title Derivative-free discrete gradient methods
topic Numerical Analysis
Primary 65L99, Secondary 65L12
url https://arxiv.org/abs/2601.07479