Improving multilevel Monte Carlo for stochastic differential equations with application to the Langevin equation

DOI10.1098/rspa.2014.0679zbMath1372.65020arXiv1409.2342OpenAlexW2161444103WikidataQ52388865 ScholiaQ52388865MaRDI QIDQ5362397

Tony Shardlow, Eike H. Müller, Robert Scheichl

Publication date: 29 September 2017

Published in: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1409.2342

Mathematics Subject Classification ID

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Weak approximation of SDEs for tempered distributions and applications ⋮ Numerical solution of the Fokker-Planck equation using physics-based mixture models ⋮ Multilevel Monte Carlo and improved timestepping methods in atmospheric dispersion modelling ⋮ Classical Langevin dynamics derived from quantum mechanics ⋮ Multilevel ensemble Kalman filtering for spatio-temporal processes ⋮ Random bit multilevel algorithms for stochastic differential equations ⋮ Multi-index ensemble Kalman filtering ⋮ Asymptotic Analysis of Multilevel Best Linear Unbiased Estimators ⋮ Analysis of Nested Multilevel Monte Carlo Using Approximate Normal Random Variables ⋮ Improved efficiency of multilevel Monte Carlo for stochastic PDE through strong pairwise coupling

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