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Learning Equilibrium Fluctuation Expansions from Overdamped Langevin Dynamics

Probability 2026-04-07 v1

Abstract

We study higher-order small-noise fluctuation expansions for the overdamped Langevin dynamics in a quartic double-well potential. Assuming that the initial data admits a suitable expansion structure, we obtain a strong dynamical expansion of the trajectories, as well as an expansion of the laws with respect to smooth observables. We then investigate the long-time behavior of the expansion coefficients. In the scalar case d=1d=1, each coefficient converges exponentially fast to a finite limit as tt\to\infty. In contrast, for d2d\ge 2, the fluctuation expansion coefficients reflect the degeneracy of the manifold of minima, which in general prevents the existence of a finite long-time limit. Furthermore, by combining a multi-level induction with combinatorial arguments, we derive a recursive formula for the fluctuation expansion coefficients. This recursion shows that the long-time limits of these dynamical expansion coefficients coincide with those arising from the corresponding equilibrium expansions.

Keywords

Cite

@article{arxiv.2604.04100,
  title  = {Learning Equilibrium Fluctuation Expansions from Overdamped Langevin Dynamics},
  author = {Lin Wang and Zhengyan Wu},
  journal= {arXiv preprint arXiv:2604.04100},
  year   = {2026}
}

Comments

32 pages

R2 v1 2026-07-01T11:54:27.282Z