AI & ML
Stochastic processes on reductive homogeneous and symmetric spaces
arXiv cs.NA0 views
arXiv:2610.42025v1 Announce Type: cross Abstract: In this paper we present a method to effectively and efficiently provide pathwise approximations of the Riemannian Brownian motion on a reductive homogeneous space $M\cong G/H$ endowed with a $G$-invariant metric. This setting includes spheres, hyperbolic spaces, the space of symmetric positive-definite matrices, flag manifolds and Stiefel manifolds. The simulation is based on Wong--Zakai approximations of an appropriately chosen SDE in $G$ that is projected down onto $M\cong G/H$. The effectiveness lies in the fact that well-established results on the convergence rate of the Wong--Zakai equation immediately carry over to the homogeneous space thanks to Nash's embedding. The efficiency lies in the fact that explicit representations of the Wong--Zakai approximations can be obtained in this setting using the Lie exponential map.
Source:https://arxiv.org/abs/2610.42025PreviousNumerical evaluation of one-loop integrals using quadrature rulesNextStochastic Rayleigh-Ritz Ascent: Global Linear Convergence under a Spectral Gap
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