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High Order Numerical Approximation of the Invariant Measure of Ergodic SDEs

Zygalakis, Konstantinos C.
Published in SIAM Journal on Numerical Analysis. 2014, vol. 52, no. 4, p. 1600-1622
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.
Keywords Stochastic differential equationsWeak convergenceModified differential equationsBackward error analysisInvariant measureErgodicity
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Article (Accepted version) (5.8 MB) - public document Free access
Research group Analyse numérique
FNS: 200020 144313/1
(ISO format)
ABDULLE, Assyr, VILMART, Gilles, ZYGALAKIS, Konstantinos C. High Order Numerical Approximation of the Invariant Measure of Ergodic SDEs. In: SIAM Journal on Numerical Analysis, 2014, vol. 52, n° 4, p. 1600-1622. doi: 10.1137/130935616 https://archive-ouverte.unige.ch/unige:41847

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Deposited on : 2014-11-14

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