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This paper presents a model reduction method for the class of linear quantum stochastic systems often encountered in quantum optics and their related fields. The approach is proposed on the basis of an interpolatory projection ensuring that…

Quantum Physics · Physics 2015-09-21 O. Techakesari , H. I. Nurdin

Here the polynomial interpolation approach is used to introduce the main results on multivariate normal algebraic systems. Next we bring a construction which shows that any standard algebraic system, with finite set of solutions, can be…

Numerical Analysis · Mathematics 2025-10-20 H. Hakopian

Port-Hamiltonian (pH) systems are a very important modeling tool in almost all areas of systems and control, in particular in network based model of multi-physics multi-scale systems. They lead to remarkably robust models that can be easily…

Optimization and Control · Mathematics 2019-03-19 Karim Cherifi , Volker Mehrmann , Kamel Hariche

While reduced-order models (ROMs) have been popular for efficiently solving large systems of differential equations, the stability of reduced models over long-time integration is of present challenges. We present a greedy approach for ROM…

Numerical Analysis · Mathematics 2018-03-20 Babak Maboudi Afkham , Jan S. Hesthaven

In this contribution, we propose a detailed study of interpolation-based data-driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer…

Numerical Analysis · Mathematics 2023-01-13 Quirin Aumann , Ion Victor Gosea

We provide a fully nonlinear port-Hamiltonian formulation for discrete elastodynamical systems as well as a structure-preserving time discretization. The governing equations are obtained in a variational manner and represent index-1…

Dynamical Systems · Mathematics 2025-06-23 Philipp L. Kinon , Tobias Thoma , Peter Betsch , Paul Kotyczka

We provide first the functional analysis background required for reduced order modeling and present the underlying concepts of reduced basis model reduction. The projection-based model reduction framework under affinity assumptions,…

Numerical Analysis · Mathematics 2023-08-30 Gianluigi Rozza , Martin Hess , Giovanni Stabile , Marco Tezzele , Francesco Ballarin

We formulate here an approach to model reduction that is well-suited for linear time-invariant control systems that are stabilizable and detectable but may otherwise be unstable. We introduce a modified $\mathcal{H}_2$-error metric, the…

Numerical Analysis · Mathematics 2019-10-01 Tobias Breiten , Chris A. Beattie , Serkan Gugercin

This work introduces a surrogate-based model for efficiently estimating the frequency response of dynamic mechanical metamaterials, particularly when dealing with large parametric perturbations and aperiodic substructures. The research…

Computational Engineering, Finance, and Science · Computer Science 2025-11-06 J. Pereira , R. O. Ruiz

In this paper we design discrete port-Hamiltonian systems systematically in two different ways, by applying discrete gradient methods and splitting methods respectively. The discrete port-Hamiltonian systems we get satisfy a discrete notion…

Numerical Analysis · Mathematics 2017-06-28 Elena Celledoni , Eirik Hoel Høiseth

The reduction of Hamiltonian systems aims to build smaller reduced models, valid over a certain range of time and parameters, in order to reduce computing time. By maintaining the Hamiltonian structure in the reduced model, certain…

Numerical Analysis · Mathematics 2024-09-17 Raphaël Côte , Emmanuel Franck , Laurent Navoret , Guillaume Steimer , Vincent Vigon

Projection-based model order reduction of dynamical systems usually introduces an error between the high-fidelity model and its counterpart of lower dimension. This unknown error can be bounded by residual-based methods, which are typically…

Numerical Analysis · Mathematics 2023-03-31 Johannes Rettberg , Dominik Wittwar , Patrick Buchfink , Robin Herkert , Jörg Fehr , Bernard Haasdonk

In this paper, we consider the structure-preserving model order reduction problem for multi-input/multi-output bilinear control systems by tangential interpolation. We propose a new type of tangential interpolation problem for structured…

Numerical Analysis · Mathematics 2023-11-16 Peter Benner , Serkan Gugercin , Steffen W. R. Werner

This paper develops an interpolatory framework for weighted-$\mathcal{H}_2$ model reduction of MIMO dynamical systems. A new representation of the weighted-$\mathcal{H}_2$ inner products in MIMO settings is introduced and used to derive…

Systems and Control · Computer Science 2016-10-05 Tobias Breiten , Christopher Beattie , Serkan Gugercin

Port-Hamiltonian systems provide an energy-based formulation with a model class that is closed under structure preserving interconnection. For continuous-time systems these interconnections are constructed by geometric objects called Dirac…

Optimization and Control · Mathematics 2023-08-21 Karim Cherifi , Hannes Gernandt , Dorothea Hinsen , Volker Mehrmann

A fluid-structure interaction model in a port-Hamiltonian representation is derived for a classical guitar. We combine the laws of continuum mechanics for solids and fluids within a unified port-Hamiltonian (pH) modeling approach by…

This paper presents a systematic methodology for the discretization and reduction of a class of one-dimensional Partial Differential Equations (PDEs) with inputs and outputs collocated at the spatial boundaries. The class of system that we…

Numerical Analysis · Mathematics 2024-07-02 Jesus-Pablo Toledo-Zucco , Denis Matignon , Charles Poussot-Vassal , Yann Le Gorrec

We propose a linearly implicit structure-preserving numerical method for semilinear Hamiltonian systems with polynomial nonlinearities, combining Kahan's method and exponential integrator. This approach efficiently balances computational…

Numerical Analysis · Mathematics 2026-03-03 Pan Zhang , Fengyang Xiao , Lu Li

This paper reports a development in the proper symplectic decomposition (PSD) for model reduction of forced Hamiltonian systems. As an analogy to the proper orthogonal decomposition (POD), PSD is designed to build a symplectic subspace to…

Numerical Analysis · Mathematics 2016-03-14 Liqian Peng , Kamran Mohseni

We propose a discretization of vector fields that are Hamiltonian up to multiplication by a positive function on the phase space that may be interpreted as a time reparametrization. We prove that our method is structure preserving in the…

Numerical Analysis · Mathematics 2020-08-18 Luis C. García-Naranjo , Mats Vermeeren