Tangent Space Parametrization for Stochastic Differential Equations on SO(n)
Preprint
Abstract
In this paper, we study the numerical simulation of stochastic differential equations (SDEs) on the special orthogonal Lie group $\text{SO}(n)$. We propose a geometry-preserving numerical scheme based on the stochastic tangent space parametrization (S-TaSP) method for state-dependent multiplicative SDEs on $\text{SO}(n)$. The convergence analysis of the S-TaSP scheme establishes a strong convergence order of $\mathcal{O}(δ^{\frac{1-ε}{2}})$, which matches the convergence order of the previous stochastic Lie Euler-Maruyama scheme while avoiding the computational cost of the exponential map. Numerical simulation illustrates the theoretical results.
Keywords
All Related Versions
This publication has 6 references indexed in Scilit:
- Curved schemes for stochastic differential equations on, or near, manifoldsProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2022
- Simultaneous Feedback and Feedforward Control and Its Application to Realize a Random Walk on the Bloch Sphere in an Xmon-Superconducting-Qubit SystemPhysical Review Applied, 2020
- Numerical Methods for Stochastic Differential Equations in Matrix Lie Groups Made SimpleIEEE Transactions on Automatic Control, 2018
- Geometric Euler--Maruyama Schemes for Stochastic Differential Equations in SO(n) and SE(n)SIAM Journal on Numerical Analysis, 2016
- An Algorithmic Introduction to Numerical Simulation of Stochastic Differential EquationsSIAM Review, 2001
- An introduction to numerical methods for stochastic differential equationsActa Numerica, 1999