
arXiv: 2601.07479
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.
18 pages, 7 figures
Finite difference and finite volume methods for ordinary differential equations, energy preservation, derivative-free numerical integration, Numerical Analysis, discrete gradients, Primary 65L99, Secondary 65L12, FOS: Mathematics, Numerical Analysis (math.NA), Hamiltonian systems, Numerical methods for Hamiltonian systems including symplectic integrators
Finite difference and finite volume methods for ordinary differential equations, energy preservation, derivative-free numerical integration, Numerical Analysis, discrete gradients, Primary 65L99, Secondary 65L12, FOS: Mathematics, Numerical Analysis (math.NA), Hamiltonian systems, Numerical methods for Hamiltonian systems including symplectic integrators
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
