In mathematics — specifically, in stochastic analysis — the Green measure is a measure associated to an Ità  diffusion. There is an associated Green formula representing suitably smooth functions in terms of the Green measure and first exit times of the diffusion. The concepts are named after the British mathematician George Green and are generalizations of the classical Green's function and Green formula to the stochastic case using Dynkin's formula.
Let X be an R<sup>n</sup>-valued Ità  diffusion satisfying an Ità  stochastic differential equation of the form
Let P<sup>x</sup> denote the law of X given the initial condition X<sub>0</sub> = x, and let E<sup>x</sup> denote expectation with respect to P<sup>x</sup>. Let L<sub>X</sub> be the infinitesimal generator of X, i.e.
Let D ⊆ R<sup>n</sup> be an open, bounded domain; let τ<sub>D</sub> be the first exit time of X from D:
Intuitively, the Green measure of a Borel set H (with respect to a point x and domain D) is the expected length of time that X, having started at x, stays in H before it leaves the domain D. That is, the Green measure of X with respect to D at x, denoted G(x, â ), is defined for Borel sets H ⊆ R<sup>n</sup> by
or for bounded, continuous functions f : D â R by
The name "Green measure" comes from the fact that if X is Brownian motion, then
where G(x, y) is Green's function for the operator L<sub>X</sub> (which, in the case of Brownian motion, is ÃÂ, where ÃÂ is the Laplace operator) on the domain D.
Suppose that E<sup>x</sup>[τ<sub>D</sub>] < +∞ for all x ∈ D, and let f : R<sup>n</sup> â R be of smoothness class C<sup>2</sup> with compact support. Then
In particular, for C<sup>2</sup> functions f with support compactly embedded in D,
The proof of Green's formula is an easy application of Dynkin's formula and the definition of the Green measure: