Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport
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.
- Publication:
-
arXiv e-prints
- Pub Date:
- June 2020
- DOI:
- 10.48550/arXiv.2006.11106
- arXiv:
- arXiv:2006.11106
- Bibcode:
- 2020arXiv200611106P
- Keywords:
-
- Physics - Computational Physics;
- Physics - Plasma Physics