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Numerical Methods for Stochastic Differential Equations in Stiefel Manifolds via the Cayley Transform

机译:通过Cayley变换在Stiefel歧管中随机微分方程的数值方法

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Stochastic differential equations evolving in a Stiefel manifold occur in several applications in Science and Engineering. For ordinary differential equations evolving in Stiefel manifolds there is a solid literature on numerical implementation guaranteeing adherence to the manifold. But for stochastic differential equations, numerical methods are in their infancy. Indeed some existing schemes fail to satisfy the required geometric constraints. We develop a new and efficient scheme to simulate a stochastic differential equation evolving in a Stiefel manifold, based on the Cayley transform. In particular, we show how to construct drift and diffusion terms to obey geometric conditions, ensuring evolution in the Stiefel manifold. Comparative simulations illustrate the new scheme showing that it is geometry preserving over large numbers of time steps.
机译:在Stiefel歧管中发展的随机微分方程发生在科学和工程的几种应用中。对于在Stiefel歧管中发展的常微分方程,在数值实施方面存在实心文献,保证歧义歧管。但对于随机微分方程,数值方法在其初期内。实际上,一些现有方案无法满足所需的几何约束。我们开发了一种新的和高效的方案来模拟基于Cayley变换的Stiefel歧管中的随机微分方程。特别是,我们展示了如何构建漂移和扩散术语来遵守几何条件,确保Stiefel歧管中的演变。比较仿真说明了新方案,表明它是在大量时间步骤中保留的几何形状。

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