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arxiv: 1206.2937 · v1 · pith:KR2MVB7Unew · submitted 2012-06-13 · 🧮 math.PR · math.AP

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

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

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