Special Session 37: Recent development of stochastic optimal control, applications and deep learning methods

Stability analysis of a branching diffusion solver for semilinear heat equations
Nicolas Privault
Nanyang Technological University
Singapore
Co-Author(s):    Qiao Huang and Nicolas Privault
Abstract:
Stochastic branching algorithms provide a useful alternative to grid-based schemes for the numerical solution of partial differential equations, particularly in high-dimensional settings. However, they require a strict control of the integrability of random functionals of branching processes in order to ensure the non-explosion of solutions. In this paper, we study the stability of a functional branching representation of PDE solutions by deriving sufficient criteria for the integrability of the multiplicative weighted progeny of stochastic branching processes. We also prove the uniqueness of mild solutions under uniform integrability assumptions on random functionals.