Stable and efficient numerical methods for Stochastic Differential Equations (Subprojekt des DK W-1214)

The need to model with and thus to treat stochastic ordinary and partial differential equations numerically has emerged in many different application areas, such as computational finance, chemical kinetics, laser dynamics, neuroscience, molecular dynamics or electrical circuits. Having developed numerical methods and established their convergence, it is imperative to understand the qualitative properties of these methods in order to be able to choose particular methods and/or their parameters such that the resulting solvers are reliable and efficient. In this project we aim to develop further understanding of appropriate concepts and tools to describe and ascertain structural properties of numerical methods for stochastic ordinary/partial differential equations.