Kaarnioja, VesaKazashi, YoshihitoKuo, Frances Y.Nobile, FabioSloan, Ian H.2021-12-182021-12-182021-12-18202210.1007/s00211-021-01242-3https://infoscience.epfl.ch/handle/20.500.14299/183879WOS:000724094100001This paper deals with the kernel-based approximation of a multivariate periodic function by interpolation at the points of an integration lattice-a setting that, as pointed out by Zeng et al. (Monte Carlo and Quasi-Monte Carlo Methods 2004, Springer, New York, 2006) and Zeng et al. (Constr. Approx. 30: 529-555, 2009), allows fast evaluation by fast Fourier transform, so avoiding the need for a linear solver. The main contribution of the paper is the application to the approximation problem for uncertainty quantification of elliptic partial differential equations, with the diffusion coefficient given by a random field that is periodic in the stochastic variables, in the model proposed recently by Kaarnioja et al. (SIAM J Numer Anal 58(2): 1068-1091, 2020). The paper gives a full error analysis, and full details of the construction of lattices needed to ensure a good (but inevitably not optimal) rate of convergence and an error bound independent of dimension. Numerical experiments support the theory.Mathematics, AppliedMathematics41a1541a6365d0765d1565t40monte carlo integrationelliptic pdesspacestext::journal::journal article::research article