Building on previous research which generalized multilevel Monte Carlo methods using either sparse grids or Quasi-Monte Carlo methods, this paper considers the combination of all these ideas applied to elliptic PDEs with finite-dimensional uncertainty in the coefficients. It shows the potential for the computational cost to achieve an O(ε) r.m.s. accuracy to be O(ε-r) with r<2, independently of the spatial dimension of the PDE.
CITATION STYLE
Giles, M. B., Kuo, F. Y., & Sloan, I. H. (2018). Combining sparse grids, multilevel MC and QMC for elliptic PDEs with random coefficients. In Springer Proceedings in Mathematics and Statistics (Vol. 241, pp. 265–281). Springer New York LLC. https://doi.org/10.1007/978-3-319-91436-7_14
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