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"Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds and Approximation with Weakly Symplectic Autoencoder" published in SISC
New Article (March 2023) -
"Randomized Symplectic Model Order Reduction for Hamiltonian Systems"
New Preprint (March 2023) -
"Improved a posteriori Error Bounds for Reduced port-Hamiltonian Systems"
New Preprint (March 2023) -
Two PhD or PostDoc positions at the NMH-group of Prof. B. Stamm
The NMH-group offers following positions: -
Congratulations to Robin Merkle
Robin Merkle successfully defended his Ph.D. thesis.
Our research and teaching address a wide range of directions in modern applied mathematics: Mathematical modelling, applied analysis, stochastic techniques and scientific computing provide the theoretical and practical background to understand, predict and optimise highly complex processes in engineering, life, social and natural sciences. Numerical simulation has become the key technology to address these core questions of the University’s scientific and strategic orientation.
Our research involves developing, analyzing and implementing new numerical techniques in both problem-specific and more fundamental settings, and we are equally interested in multidisciplinary applications and theoretical foundations, connecting engineering, natural and computer sciences. We are involved in various national, international and industrial collaborations.
See below for more detailed information about our Institute.

Dominik Göddeke
Prof. Dr. rer. nat.Head of Institute and Head of Group

Britta Lenz
Secretary's Office