Numerical Analysis of Automodel Solutions for Superdiffusive Transport
For researchers studying superdiffusive transport, this work provides validated approximate solutions, though it is an incremental extension of known methods.
The paper verifies the high accuracy of approximate automodel solutions for the Green's function of superdiffusive transport with Lévy flights, using distributed computing experiments. The results confirm accuracy across a wide range of space-time variables.
The distributed computing analysis of the accuracy of automodel solutions for the Green's function of a wide class of superdiffusive transport of perturbation on a uniform background is carried out. The approximate automodel solutions have been suggested for the 1D transport equation with a model long-tailed step-length probability distribution function (PDF) with various power-law exponents. These PDFs describe the transport dominated by the Lévy flights. Massive computing experiments were done to verify automodel solutions. The Everest distributed computing platform and the cluster at NRC Kurchatov Institute were used. The results verify the high accuracy of automodel solutions in a wide range of space-time variables and suggest extending the developed method of automodel solutions to a wider class of stochastic phenomena.