Research Paper#Computational Physics, Numerical Methods, Optimal Transport🔬 ResearchAnalyzed: Jan 3, 2026 08:55
Newton-Krylov for Steady States of Particle Simulations via Optimal Transport
Published:Dec 31, 2025 02:22
•1 min read
•ArXiv
Analysis
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.
Key Takeaways
- •Applies optimal transport to stochastic particle simulations.
- •Enables the use of Newton-Krylov solvers for steady-state computation.
- •Handles high noise regimes effectively.
- •Introduces smooth (I)CDF timesteppers.
- •Provides a unified variational framework for both deterministic and stochastic systems.
Reference
“The paper introduces smooth cumulative- and inverse-cumulative-distribution-function ((I)CDF) timesteppers that evolve distributions rather than particles.”