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On annealed elliptic Green function estimates

Abstract

We consider a random, uniformly elliptic coefficient field aa on the lattice Zd\mathbb{Z}^d. The distribution \langle \cdot \rangle of the coefficient field is assumed to be stationary. Delmotte and Deuschel showed that the gradient and second mixed derivative of the parabolic Green function G(t,x,y)G(t,x,y) satisfy optimal annealed estimates which are L2L^2 resp. L1L^1 in probability, i.e. they obtained bounds on xG(t,x,y)212\langle |\nabla_x G(t,x,y)|^2 \rangle^{\frac{1}{2}} and xyG(t,x,y)\langle |\nabla_x \nabla_y G(t,x,y)| \rangle, see T. Delmotte and J.-D. Deuschel: On estimating the derivatives of symmetric diffusions in stationary random environments, with applications to the ϕ\nabla\phi interface model, Probab. Theory Relat. Fields 133 (2005), 358--390. In particular, the elliptic Green function G(x,y)G(x,y) satisfies optimal annealed bounds. In a recent work, the authors extended these elliptic bounds to higher moments, i.e. LpL^p in probability for all p<p<\infty, see D. Marahrens and F. Otto: {Annealed estimates on the Green function}, arXiv:1304.4408 (2013). In this note, we present a new argument that relies purely on elliptic theory to derive the elliptic estimates (see Proposition 1.2 below) for xG(x,y)212\langle |\nabla_x G(x,y)|^2 \rangle^{\frac{1}{2}} and xyG(x,y)\langle |\nabla_x \nabla_y G(x,y)| \rangle.Comment: 15 page

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