A PARALLEL ITERATIVE PROBABILISTIC METHOD FOR MIXED PROBLEMS OF LAPLACE EQUATIONS WITH THE FEYNMAN-KAC FORMULA OF KILLED BROWNIAN MOTIONS.

In this paper, a parallel probabilistic method using the Feynman--Kac formula of killed Brownian motions is proposed to solve the mixed boundary value problems (BVPs) of 3D Laplace equations. To avoid using reflecting Brownian motions and the calculation of their local time L(t) in the Feynman--Kac representation of solutions for Neumann and Robin BVPs, the proposed method uses an iterative approach to approximate the solutions where each iteration will use the Feynman--Kac formula to solve a pure Dirichlet problem, thus only involving killed Brownian motions. First, the boundary of the domain is decomposed with overlapping local patches formed by the intersection of hemispheres superimposed on the domain boundary. The iteration starts with an arbitrary initial guess for the Dirichlet data on the Neumann and Robin boundaries; then, using the Feynman--Kac formula for a pure Dirichlet problem with the current available Dirichlet data on the whole boundary, the solution over the hemispheres can be obtained by the Feynman--Kac formula for the killed Brownian motions, sampled by a walk-on-spheres (WOS) algorithm. Second, by solving a local boundary integral equation (BIE) over each hemisphere and a local patch on the domain boundary, the Dirichlet data on the Neumann and Robin boundaries can be updated. By continuing this process, the proposed hybrid probabilistic and deterministic BIE-WOS method gives a highly parallel algorithm for the global solution of any mixed-type BVPs of the Laplace equations. Numerical results of various mixed interior and exterior BVPs demonstrate the parallel efficiency and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]