English

Pathwise estimates for an effective dynamics

Probability 2016-05-10 v1

Abstract

Starting from the overdamped Langevin dynamics in Rn\mathbb{R}^n, dXt=V(Xt)dt+2β1dWt, dX_t = -\nabla V(X_t) dt + \sqrt{2 \beta^{-1}} dW_t, we consider a scalar Markov process ξt\xi_t which approximates the dynamics of the first component Xt1X^1_t. In the previous work [F. Legoll, T. Lelievre, Nonlinearity 2010], the fact that (ξt)t0(\xi_t)_{t \ge 0} is a good approximation of (Xt1)t0(X^1_t)_{t \ge 0} is proven in terms of time marginals, under assumptions quantifying the timescale separation between the first component and the other components of XtX_t. Here, we prove an upper bound on the trajectorial error E(sup0tTXt1ξt)\mathbb{E} \left( \sup_{0 \leq t \leq T} \left| X^1_t - \xi_t \right| \right), for any T>0T > 0, under a similar set of assumptions. We also show that the technique of proof can be used to obtain quantitative averaging results.

Keywords

Cite

@article{arxiv.1605.02644,
  title  = {Pathwise estimates for an effective dynamics},
  author = {Frederic Legoll and Tony Lelievre and Stefano Olla},
  journal= {arXiv preprint arXiv:1605.02644},
  year   = {2016}
}