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Order Conditions for Sampling the Invariant Measure of Ergodic Stochastic Differential Equations on Manifolds

Adrien Laurent, Gilles Vilmart

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Source: Crossref

Published: Jun 7, 2021

DOI: 10.1007/s10208-021-09495-y

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Source abstract

Abstract We derive a new methodology for the construction of high-order integrators for sampling the invariant measure of ergodic stochastic differential equations with dynamics constrained on a manifold. We obtain the order conditions for sampling the invariant measure for a class of Runge–Kutta methods applied to the constrained overdamped Langevin equation. The analysis is valid for arbitrarily high order and relies on an extension of the exotic aromatic Butcher-series formalism. To illustrate the methodology, a method of order two is introduced, and numerical experiments on the sphere, the torus and the special linear group confirm the theoretical findings.

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Order Conditions for Sampling the Invariant Measure of Ergodic Stochastic Differential Equations on Manifolds — Mathematical Frontier Network