Geometric Milstein Scheme for Stochastic Differential Equations on SO(n) and SE(n)

TL;DR

This paper introduces a novel higher-order numerical scheme for stochastic differential equations on SO(n) and SE(n), preserving geometric structure and achieving strong convergence of order 1.

Contribution

It extends the tangent space parameterization framework to stochastic settings, enabling higher-order, geometry-preserving SDE integrators on Lie groups.

Findings

The scheme achieves strong convergence of order 1.

Numerical experiments confirm efficiency and robustness.

The method outperforms existing Lie group integrators.

Abstract

In the paper, we propose a higher-order geometry-preserving numerical method for stochastic differential equations (SDEs) evolving on the Lie groups SO(n) and SE(n). Most existing Lie group integrators rely on Magnus expansion of the exponential map, which makes the construction of higher-order stochastic schemes difficult. To overcome this limitation, we develop a tangent-space parameterization corrected Milstein method (TaSP-CM), extending the tangent space parameterization (TaSP) framework from Lie-group ODEs to the stochastic setting. Although TaSP is a well-established method for Lie ODEs, the extension to SDEs is non-trivial and requires new stochastic corrections that ensure both geometric consistency and higher-order accuracy. We prove that the proposed scheme achieves strong convergence of order 1 under both commutative and non-commutative noise. Numerical experiments illustrate the theoretical results and demonstrate the efficiency and robustness of the proposed method.