Dynamical Properties of Coarse-Grained Stochastic Dynamics

Thomas Hudson

School of Mathematics, University of Warwick

Model-reduction, or coarse-graining, refers to the process of taking a model governing many degrees of freedom and approximating it by a model with a lower number of degrees of freedom. For complex models such as those used in molecular dynamics, the process of coarse-graining enables longer and larger simulations with given computational resources, and so is frequently used by practitioners. Motivated by this application, I will discuss the coarse-graining of linear stochastic dynamical systems, providing a framework within which one may evaluate the accuracy of a coarse-grained model. I will then present recent rigorous mathematical results on the dynamical accuracy of coarse-grained systems in this context obtained with Helen Li.