We published a new preprint on "Randomized Symplectic Model Order Reduction for Hamiltonian Systems" on arXiv in collaboration with our colleagues from the Institute of Engineering and Computational Mechanics at the University of Stuttgart. In this work, we show how symplectic structure preserving basis generation can be made more efficient with randomized matrix factorizations. We present a randomized complex SVD (rcSVD) algorithm and a randomized SVD-like (rSVD-like) decomposition. We demonstrate the efficiency of the approaches with numerical experiments on high-dimensional systems.
Randomized Symplectic Model Order Reduction for Hamiltonian Systems