2025-12-07 Sunday Sign in CN

Activities
Solving bivariate kinetic equations for polymer diffusion using deep learning
Home - Activities
Reporter:
邓伟华 教授 (兰州大学)
Inviter:
崔涛 研究员
Subject:
Solving bivariate kinetic equations for polymer diffusion using deep learning
Time and place:
12月5日(周五)15:00-16:00,南楼229
Abstract:

We derive a class of backward stochastic differential equations (BSDEs) for infinite dimensionally coupled nonlinear parabolic partial differential equations, thereby extending the deep BSDE method. In addition, we model a class of polymer dynamics accompanied by polymerization and depolymerization reactions, and derive the corresponding Fokker-Planck equations and Feynman-Kac equations. Due to chemical reactions, the system exhibits a Brownian yet non-Gaussian phenomenon, and the resulting equations are infinitely dimensionally coupled. We solve these equations numerically through our new deep BSDE method, and also solve a class of high-dimensional nonlinear equations, which verifies the effectiveness and shows approximation accuracy of the algorithm.