Splitting algorithms for paraxial and Itô-Schrödinger models of wave propagation in random media
It provides a theoretically valid numerical method for wave propagation in random media under challenging scale conditions, benefiting computational physics and engineering applications.
This paper proposes a full discretization for wave beam propagation in random media using paraxial or Itô-Schrödinger models, achieving mean-square convergence of order Δz and error on statistical moments of order (Δz)^2 even when the wavelength is much smaller than the step size, a regime where standard splitting schemes fail.
This paper introduces a full discretization procedure to solve wave beam propagation in random media modeled by a paraxial wave equation or an Itô-Schrödinger stochastic partial differential equation. This method bears similarities with the phase screen method used routinely to solve such problems. The main axis of propagation is discretized by a centered splitting scheme with step $Δz$ while the transverse variables are treated by a spectral method after appropriate spatial truncation. The originality of our approach is its theoretical validity even when the typical wavelength $θ$ of the propagating signal satisfies $θ\llΔz$. More precisely, we obtain a convergence of order $Δz$ in mean-square sense while the errors on statistical moments are of order $(Δz)^2$ as expected for standard centered splitting schemes. This is a surprising result as splitting schemes typically do not converge when $Δz$ is not the smallest scale of the problem. The analysis is based on equations satisfied by statistical moments in the Itô-Schrödinger case and on integral (Duhamel) expansions for the paraxial model. Several numerical simulations illustrate and confirm the theoretical findings.