CASUS Institute Seminar
POSTPONED: Discovery and model reduction of Hamiltonian systems
CASUS Institute Seminar, Prof. Peter Benner, Director (currently Managing Director), Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
Originally planned for June 2026, the talk had to be postponed on short notice. A new date, likely in autumn 2026, will be communicated in the coming weeks.
Abstract of the talk// An often encountered computational issue in studying physical systems with conservative properties is the solution of high-dimensional Hamiltonian systems. These arise either direct from modeling, e.g., in molecular dynamics or celestial mechanics, or from structure-preserving discretizations of Hamiltonian PDEs like the wave, Maxwell, or Vlasov equations, describing, respectively, the propagation of waves, electromagnetic systems or plasma physics. Fast simulation under varying conditions requires learning a compact, reduced-order model that is fast to simulate and faithfully reproduces the kinetics of the full-order model. Peter will discuss several approaches to learn Hamiltonian systems from data. Model reduction can be achieved using variational autoencoders. He shows, among other, how the underlying Hamiltonian structure, resulting in a symplectic flow field, can be preserved using symplectic convolutional neural networks.
CV// Peter received the Diploma in mathematics from the RWTH Aachen University, Aachen, Germany, in 1993. From 1993 to 1997, he worked toward the Ph.D. at the University of Kansas, Lawrence, KS, USA, and the TU Chemnitz-Zwickau, Germany, where he received the Ph.D. in Mathematics in February 1997. In 2001, he obtained the Habilitation (Venia Legendi) in Mathematics from the University of Bremen (Germany). After spending a term as Visiting Associate Professor with the TU Hamburg-Hamburg he was a Lecturer in Mathematics with the TU Berlin from 2001 to 2003. 2003-2023 he has been a Professor for Mathematics in Industry and Technology with the TU Chemnitz. In 2010, he was appointed as one of the four Directors of the Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. Since 2011, he has also been an Honorary Professor with the Otto-von-Guericke University of Magdeburg, Germany. He is a SIAM Fellow (Class of 2017) and member of acatech – the German Academy of Science and Engineering.
Peter’s research interests include scientific computing, numerical mathematics, systems theory, optimal control, and machine learning. A particular emphasis has been on applying methods from numerical linear algebra and matrix theory in systems and control theory. Recent research focuses on numerical methods for optimal control of systems modeled by evolution equations (PDEs, DAEs, SPDEs), model order reduction, preconditioning in optimal control and UQ problems, and Krylov subspace methods for structured or quadratic eigenproblems. More recently, he has become interested in scientific machine learning, with a focus on equation discovery for dynamical systems from time series data. Research in all these areas is accompanied by the development of algorithms and mathematical software suitable for modern and high-performance computer architectures.
Peter Benner will be talking live in Görlitz. However, as the event is organized in a hybrid format that includes a videoconferencing tool by Zoom Inc., people not present in Görlitz and interested in the topic have the chance to also join the talk. Please ask for the login details via contact@casus.science.
CASUS – Center for Advanced Systems Understanding, Conrad-Schiedt-Str. 20, D-02826 Görlitz, Deutschland
tbd