TY - INPR A1 - Breiten, Tobias A1 - Unger, Benjamin T1 - Passivity preserving model reduction via spectral factorization N2 - We present a novel model-order reduction (MOR) method for linear time-invariant systems that preserves passivity and is thus suited for structure-preserving MOR for port-Hamiltonian (pH) systems. Our algorithm exploits the well-known spectral factorization of the Popov function by a solution of the Kalman-Yakubovich-Popov (KYP) inequality. It performs MOR directly on the spectral factor inheriting the original system’s sparsity enabling MOR in a large-scale context. Our analysis reveals that the spectral factorization corresponding to the minimal solution of an associated algebraic Riccati equation is preferable from a model reduction perspective and benefits pH-preserving MOR methods such as a modified version of the iterative rational Krylov algorithm (IRKA). Numerical examples demonstrate that our approach can produce high-fidelity reduced-order models close to (unstructured) H2 -optimal reduced-order models. KW - passivity KW - port-Hamiltonian systems KW - structure-preserving model order reduction KW - spectral factorization KW - H2-optimal Y1 - 2021 ER -