Krylov projection methods for linear Hamiltonian systems
arXiv:1808.066744 citationsh-index: 26
AI Analysis
For researchers in numerical linear algebra and computational physics, this work provides insight into structure-preserving model reduction for Hamiltonian systems.
The paper studies geometric properties, particularly energy preservation, of Krylov projection methods for large sparse linear Hamiltonian systems, and demonstrates their performance on Hamiltonian PDEs.
We study geometric properties of Krylov projection methods for large and sparse linear Hamiltonian systems. We consider in particular energy preservation. We discuss the connection to structure preserving model reduction. We illustrate the performance of the methods by applying them to Hamiltonian PDEs.