Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport
Computational Physics
2020-06-22 v1 Plasma Physics
Abstract
We propose a novel discrete method of constructing Gaussian Random Fields (GRF) based on a combination of modified spectral representations, Fourier and Blob. The method is intended for Direct Numerical Simulations of the V-Langevin equations. The latter are stereotypical descriptions of anomalous stochastic transport in various physical systems. From an Eulerian perspective, our method is designed to exhibit improved convergence rates. From a Lagrangian perspective, our method others a pertinent description of particle trajectories in turbulent velocity fields: the exact Lagrangian invariant laws are well reproduced. From a computational perspective, our method is twice as fast as standard numerical representations.
Keywords
Cite
@article{arxiv.2006.11106,
title = {Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport},
author = {D. I. Palade and M. Vlad},
journal= {arXiv preprint arXiv:2006.11106},
year = {2020}
}