English

Rough flows

Probability 2018-03-20 v4 Classical Analysis and ODEs

Abstract

We introduce in this work a concept of rough driver that somehow provides a rough path-like analogue of an enriched object associated with time-dependent vector fields. We use the machinery of approximate flows to build the integration theory of rough drivers and prove well-posedness results for rough differential equations on flows and continuity of the solution flow as a function of the generating rough driver. We show that the theory of semi-martingale stochastic flows developed in the 80's and early 90's fits nicely in this framework, and obtain as a consequence some strong approximation results for general semimartingale flows and provide a fresh look at large deviation theorems for 'Gaussian' stochastic flows.

Keywords

Cite

@article{arxiv.1505.01692,
  title  = {Rough flows},
  author = {I. Bailleul and S. Riedel},
  journal= {arXiv preprint arXiv:1505.01692},
  year   = {2018}
}

Comments

v4, 55 pages; final version. The exposition has been polished to make the work easier to read

R2 v1 2026-06-22T09:29:42.387Z