Green's function-stochastic methods framework for probing nonlinear evolution problems: Burger's equation, the nonlinear Schrodinger's equation, and hydrodynamic organization of near-molecular-scale vorticity
Russell G. Keanini

TL;DR
This paper introduces a novel framework combining Green's function and stochastic process techniques to analyze nonlinear evolution equations, demonstrated on Burgers' and nonlinear Schrödinger's equations, and applied to vortex sheet dynamics.
Contribution
The framework provides a new probabilistic approach to nonlinear PDEs, enabling systematic derivation of solutions and physical insights into vortex sheet evolution and organization.
Findings
Probabilistic derivation of Cole-Hopf transformation for Burgers' equation.
Recovery of known soliton solutions for nonlinear Schrödinger's equation.
Analytical descriptions of vortex sheet dynamics under various conditions.
Abstract
A framework which combines Green's function (GF) methods and techniques from the theory of stochastic processes is proposed for tackling nonlinear evolution problems. The framework, established by a series of easy-to-derive equivalences between Green's function and stochastic representative solutions of linear drift-diffusion problems, provides a flexible structure within which nonlinear evolution problems can be analyzed and physically probed. As a preliminary test bed, two canonical, nonlinear evolution problems - Burgers' equation and the nonlinear Schrodinger's equation - are first treated. In the first case, the framework provides a rigorous, probabilistic derivation of the well known Cole-Hopf ansatz. Likewise, in the second, the machinery allows systematic recovery of a known soliton solution. The framework is then applied to a fairly extensive exploration of physical features…
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