Teams

In order to get a deep insight into the underlying process, dynamics, structure or devices, modeling and simulation are unavoidable in many research and application fields. The resulting mathematical models are usually in the form of partial differential equations. To simulate such models, spatial (-time) discretization is necessary, which results in large-scale, complex systems with enormous number of equations. The simulation becomes time-consuming because of the large scale and complexity of the systems.

We study numerical methods for linear and nonlinear eigenvalue problems. This includes the development and analysis of new algorithms, (backward) error analysis, and the derivation of the associated (relative) perturbation theory.  Special attention is given to linear, generalized, and polynomial eigenproblems with spectral symmetries.
Moreover, we investigate the solution of special linear systems of equations arising in PDE control and model reduction algorithms.

Modeling and simulation of fluids in large networks is a challenging problem, especially if the simulation is used to provide solutions to optimal control problems or other optimization questions. Our first goal is to be able to simulate this systems in a stable and efficient manner as truely transient systems, considering in particular the underlying network stucture.

In times of energy transition and reproducibility crisis, the team is concerned both with the research of new algorithms for power-aware computing and with the documentation and archiving of computer-based experiments. In addition to the software, infrastructural measures for data storage according to the FAIR principles as well as the reproducible execution of experiments are investigated. An additional pillar is formed by the methods of scientific high-performance computing.