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High order numerical approximation of the invariant measure of ergodic SDEs

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A. Abdulle, G. Vilmart, and K.C. Zygalakis

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Abstract. We introduce new sufficient conditions for a numerical method to approximate with high order of accuracy the invariant measure of an ergodic system of stochastic differential equations, independently of the weak order of accuracy of the method. We then present a systematic procedure based on the framework of modified differential equations for the construction of stochastic integrators that capture the invariant measure of a wide class of ergodic SDEs (Brownian and Langevin dynamics) with an accuracy independent of the weak order of the underlying method. Numerical experiments confirm our theoretical findings.

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Key Words. stochastic differential equations, weak convergence, modified differential equations, backward error analysis, invariant measure, ergodicity.

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