English

A flow-type scaling limit for random growth with memory

Probability 2024-11-11 v3

Abstract

We study a stochastic Laplacian growth model, where a set URd\mathbf{U}\subseteq\mathbb{R}^{\mathrm{d}} grows according to a reflecting Brownian motion in U\mathbf{U} stopped at level sets of its boundary local time. We derive a scaling limit for the leading-order behavior of the growing boundary (i.e. "interface"). It is given by a geometric flow-type PDE. It is obtained by an averaging principle for the reflecting Brownian motion. We also show that this geometric flow-type PDE is locally well-posed, and its blow-up times correspond to changes in the diffeomorphism class of the growth model. Our results extend those of Dembo-Groisman-Huang-Sidoravicius '21, which restricts to star-shaped growth domains and radially outwards growth, so that in polar coordinates, the geometric flow transforms into a simple ODE with infinite lifetime. Also, we remove the "separation of scales" assumption that was taken in Dembo-Groisman-Huang-Sidoravicius '21; this forces us to understand the local geometry of the growing interface.

Keywords

Cite

@article{arxiv.2310.17572,
  title  = {A flow-type scaling limit for random growth with memory},
  author = {Amir Dembo and Kevin Yang},
  journal= {arXiv preprint arXiv:2310.17572},
  year   = {2024}
}
R2 v1 2026-06-28T13:03:00.933Z