Convex Relaxation for Fokker-Planck
Abstract
We propose an approach to directly estimate the moments or marginals for a high-dimensional equilibrium distribution in statistical mechanics, via solving the high-dimensional Fokker-Planck equation in terms of low-order cluster moments or marginals. With this approach, we bypass the exponential complexity of estimating the full high-dimensional distribution and directly solve the simplified partial differential equations for low-order moments/marginals. Moreover, the proposed moment/marginal relaxation is fully convex and can be solved via off-the-shelf solvers. We further propose a time-dependent version of the convex programs to study non-equilibrium dynamics. We show the proposed method can recover the meanfield approximation of an equilibrium density. Numerical results are provided to demonstrate the performance of the proposed algorithm for high-dimensional systems.
Keywords
Cite
@article{arxiv.2306.03292,
title = {Convex Relaxation for Fokker-Planck},
author = {Yian Chen and Yuehaw Khoo and Lek-Heng Lim},
journal= {arXiv preprint arXiv:2306.03292},
year = {2023}
}