Newton-Krylov for Steady States of Particle Simulations via Optimal Transport

This paper presents a novel approach to compute steady states of both deterministic and stochastic particle simulations. It leverages optimal transport theory to reinterpret stochastic timesteppers, enabling the use of Newton-Krylov solvers for efficient computation of steady-state distributions even in the presence of high noise. The work's significance lies in its ability to handle stochastic systems, which are often challenging to analyze directly, and its potential for broader applicability in computational science and engineering.