Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport

We propose a novel discrete method of constructing Gaussian Random Fields based on combination modified spectral representations, Fourier and Blob. The is intended for Direct Numerical Simulations the V-Langevin equations. latter are stereotypical descriptions anomalous stochastic transport in various physical systems. From an Eulerian perspective, our designed to exhibit improved convergence rates. Lagrangian offers pertinent description particle trajectories turbulent velocity fields: exact invariant laws well reproduced. computational computing time reduced by factor two comparison with Fourier-like or Blob-like methods order magnitude FFT algorithms.