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Accurately learning the temporal behavior of dynamical systems requires models with well-chosen learning biases. Recent innovations embed the Hamiltonian and Lagrangian formalisms into neural networks and demonstrate a significant…

Machine Learning · Computer Science 2021-10-04 Shaan Desai , Marios Mattheakis , David Sondak , Pavlos Protopapas , Stephen Roberts

We combine energy-stable and port-Hamiltonian (pH) systems to obtain energy-stable port-Hamiltonian (espH) systems. The idea is to extend the known energy-stable systems with an input-output port, which results in a pH formulation. One…

Numerical Analysis · Mathematics 2025-06-10 Patrick Buchfink , Silke Glas , Hans Zwart

We extend the port-Hamiltonian framework defined with respect to a Lagrangian submanifold and a Dirac structure by augmenting the Lagrangian submanifold with the space of external variables. The new pair of conjugated variables is called…

Optimization and Control · Mathematics 2024-05-03 Kaja Krhac , Bernhard Maschke , Arjan van der Schaft

Electrical circuits are present in a variety of technologies, making their design an important part of computer aided engineering. The growing number of parameters that affect the final design leads to a need for new approaches to quantify…

Computational Engineering, Finance, and Science · Computer Science 2024-04-09 Idoia Cortes Garcia , Peter Förster , Lennart Jansen , Wil Schilders , Sebastian Schöps

In the present work we formally extend the theory of port-Hamiltonian systems to include random perturbations. In particular, suitably choosing the space of flow and effort variables we will show how several elements coming from possibly…

Probability · Mathematics 2022-05-12 Francesco Cordoni , Luca Di Persio , Riccardo Muradore

Parallel simulation and control of large-scale robotic systems often rely on partitioned time stepping, yet finite-iteration coupling can inject spurious energy by violating power consistency--even when each subsystem is passive. This…

Robotics · Computer Science 2026-03-18 Qi Wei , Jianfeng Tao , Hongyu Nie , Wangtao Tan

Many dynamical systems -- from robots interacting with their surroundings to large-scale multiphysics systems -- involve a number of interacting subsystems. Toward the objective of learning composite models of such systems from data, we…

Machine Learning · Computer Science 2023-05-16 Cyrus Neary , Ufuk Topcu

We present a quantum algorithm based on repeated measurement to solve initial-value problems for nonlinear ordinary differential equations (ODEs), which may be generated from partial differential equations in plasma physics. We map a…

Quantum Physics · Physics 2025-04-30 Joseph Andress , Alexander Engel , Yuan Shi , Scott Parker

This paper addresses the regulation and trajectory-tracking problems for two classes of weakly coupled electromechanical systems. To this end, we formulate an energy-based model for these systems within the port-Hamiltonian framework. Then,…

Systems and Control · Electrical Eng. & Systems 2024-07-12 N. Javanmardi , P. Borja , M. J. Yazdanpanah , J. M. A. Scherpen

Port-Hamiltonian (PH) systems provide a framework for modeling, analysis and control of complex dynamical systems, where the complexity might result from multi-physical couplings, non-trivial domains and diverse nonlinearities. A major…

Dynamical Systems · Mathematics 2024-03-15 Philipp L. Kinon , Tobias Thoma , Peter Betsch , Paul Kotyczka

In this paper we present an extension of standard iterative splitting schemes to multiple splitting schemes for solving higher order differential equations. We are motivated by dynamical systems, which occur in dynamics of the electrons in…

Numerical Analysis · Mathematics 2012-04-17 Juergen Geiser , Thomas Zacher

This work introduces a new framework integrating port-Hamiltonian systems (PHS) and neural network architectures. This framework bridges the gap between deterministic and stochastic modeling of complex dynamical systems. We introduce new…

Mathematical Physics · Physics 2025-09-09 Luca Di Persio , Matthias Ehrhardt , Youness Outaleb , Sofia Rizzotto

Distributed Port-Hamiltonian (dPHS) theory provides a powerful framework for modeling physical systems governed by partial differential equations and has enabled a broad class of boundary control methodologies. Their effectiveness, however,…

Systems and Control · Electrical Eng. & Systems 2026-04-07 Thomas Beckers , Leonardo Colombo

In this paper, we propose an orbital iteration based parallel approach for electronic structure calculations. This approach is based on our understanding of the single-particle equations of independent particles that move in an effective…

Numerical Analysis · Mathematics 2014-11-06 Xiaoying Dai , Xingao Gong , Aihui Zhou , Jinwei Zhu

The anisotropic and heterogeneous $N$-dimensional wave equation, controlled and observed at the boundary, is considered as a port-Hamiltonian system. A recent structure-preserving mixed Galerkin method is applied, leading directly to a…

Numerical Analysis · Mathematics 2022-06-01 Ghislain Haine , Denis Matignon , Anass Serhani

We examine interpolatory model reduction methods that are well-suited for treating large scale port-Hamiltonian differential-algebraic systems in a way that is able to preserve and indeed, take advantage of the underlying structural…

Numerical Analysis · Mathematics 2021-11-03 Chris A. Beattie , Serkan Gugercin , Volker Mehrmann

The relationships between port-Hamiltonian systems modeling and the notion of monotonicity are explored. The earlier introduced notion of incrementally port-Hamiltonian systems is extended to maximal cyclically monotone relations, together…

Optimization and Control · Mathematics 2022-06-22 M. Kanat Camlibel , Arjan van der Schaft

A novel strategy is proposed for the coupling of field and circuit equations when modeling power devices in the low-frequency regime. The resulting systems of differential-algebraic equations have a particular geometric structure which…

Numerical Analysis · Mathematics 2024-04-25 Herbert Egger , Idoia Cortes Garcia , Vsevolod Shashkov , Michael Wiesheu

This paper investigates the problem of data-driven modeling of port-Hamiltonian systems while preserving their intrinsic Hamiltonian structure and stability properties. We propose a novel neural-network-based port-Hamiltonian modeling…

Systems and Control · Electrical Eng. & Systems 2026-04-16 Binh Nguyen , Nam T. Nguyen , Truong X. Nghiem

Port-Hamiltonian (pH) systems have been studied extensively for linear continuous-time dynamical systems. This manuscript presents a discrete-time pH descriptor formulation for linear, completely causal, scattering passive dynamical systems…

Optimization and Control · Mathematics 2023-10-18 Karim Cherifi , Hannes Gernandt , Dorothea Hinsen , Volker Mehrmann