English

A Sublinear Variance Bound for Solutions of a Random Hamilton Jacobi Equation

Probability 2015-06-05 v1 Analysis of PDEs

Abstract

We estimate the variance of the value function for a random optimal control problem. The value function is the solution wϵw^\epsilon of a Hamilton-Jacobi equation with random Hamiltonian H(p,x,ω)=K(p)V(x/ϵ,ω)H(p,x,\omega) = K(p) - V(x/\epsilon,\omega) in dimension d2d \geq 2. It is known that homogenization occurs as ϵ0\epsilon \to 0, but little is known about the statistical fluctuations of wϵw^\epsilon. Our main result shows that the variance of the solution wϵw^\epsilon is bounded by O(ϵ/logϵ)O(\epsilon/|\log \epsilon|). The proof relies on a modified Poincar\'e inequality of Talagrand.

Keywords

Cite

@article{arxiv.1206.2937,
  title  = {A Sublinear Variance Bound for Solutions of a Random Hamilton Jacobi Equation},
  author = {Ivan Matic and James Nolen},
  journal= {arXiv preprint arXiv:1206.2937},
  year   = {2015}
}