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Explicit and Effectively Symmetric Runge-Kutta Methods

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abstract

Symmetry is a key property of numerical methods. The geometric properties of symmetric schemes make them an attractive option for integrating Hamiltonian systems, whilst their ability to exactly recover the initial condition without the need to store the entire solution trajectory makes them ideal for the efficient implementation of Neural ODEs. In this work, we present a Hopf algebraic approach to the study of symmetric B-series methods. We show that every B-series method can be written as the composition of a symmetric and "antisymmetric" component, and explore the structure of this decomposition for Runge-Kutta schemes. A major bottleneck of symmetric Runge-Kutta schemes is their implicit nature, which requires solving a nonlinear system at each step. By introducing a new set of order conditions which minimise the antisymmetric component of a scheme, we derive what we call Explicit and Effectively Symmetric (EES) schemes -- a new class of explicit Runge-Kutta schemes with near-symmetric properties. We present examples of second-order EES schemes and demonstrate that, despite their low order, these schemes readily outperform higher-order explicit schemes such as RK4 and RK5, and achieve results comparable to implicit symmetric schemes at a significantly lower computational cost.

fields

cs.CV 1 cs.LG 1

years

2026 1 2025 1

verdicts

UNVERDICTED 2

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Showing 2 of 2 citing papers.

  • Explicit and Effectively Symmetric Schemes for Neural SDEs on Lie Groups cs.LG · 2025-09-24 · unverdicted · none · ref 58 · internal anchor

    Introduces the first explicit near-reversible integrator for neural SDEs on Lie groups by extending EES schemes with Bazavov's commutator-free lift, achieving better stability and up to 10x memory reduction on manifold benchmarks.

  • Stable and Near-Reversible Diffusion ODE Solvers for Image Editing cs.CV · 2026-05-12 · unverdicted · none · ref 1 · internal anchor

    Near-reversible Runge-Kutta diffusion ODE solvers with vector-field smoothing improve stability and edit fidelity for large changes in text-guided image editing compared to exactly reversible alternatives.