Stochastic processes and boundary value problems

In mathematics, some boundary value problems can be solved using the methods of stochastic analysis.

Perhaps the most celebrated example is Shizuo Kakutani's 1944 solution of the Dirichlet problem for the Laplace operator using Brownian motion.

However, it turns out that for a large class of semi-elliptic second-order partial differential equations the associated Dirichlet boundary value problem can be solved using an Itō process that solves an associated stochastic differential equation.

be a domain (an open and connected set) in

be the Laplace operator, let

be a bounded function on the boundary

, and consider the problem: It can be shown that if a solution

at the (random) first exit point from

for a canonical Brownian motion starting at

See theorem 3 in Kakutani 1944, p. 710.

be a semi-elliptic differential operator on

of the form: where the coefficients

are continuous functions and all the eigenvalues of the matrix

Consider the Poisson problem: The idea of the stochastic method for solving this problem is as follows.

First, one finds an Itō diffusion

whose infinitesimal generator

can be taken to be the solution to the stochastic differential equation: where

is n-dimensional Brownian motion,

as above, and the matrix field

is chosen so that: For a point

denote the law of

given initial datum

denote expectation with respect to

denote the first exit time of

In this notation, the candidate solution for (P1) is: provided that

is a bounded function and that: It turns out that one further condition is required: For all

in finite time.

Under this assumption, the candidate solution above reduces to: and solves (P1) in the sense that if

denotes the characteristic operator for

satisfies (P2) and there exists a constant