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Related papers: Generalized Port-Hamiltonian DAE Systems

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The work is devoted to studying some new classical electrodynamics models of interacting charged point particles and the aspects of the quantization via the Dirac procedure related to them. Based on the vacuum field theory no-geometry…

Mathematical Physics · Physics 2009-10-07 N. N. Bogolubov , A. K. Prykarpatsky

A systematic procedure is proposed for deriving all the gauge symmetries of the general, not necessarily variational, equations of motion. For the variational equations, this procedure reduces to the Dirac-Bergmann algorithm for the…

Mathematical Physics · Physics 2015-05-13 S. L. Lyakhovich , A. A. Sharapov

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

In this paper, we propose a geometric Hamilton-Jacobi theory for systems of implicit differential equations. In particular, we are interested in implicit Hamiltonian systems, described in terms of Lagrangian submanifolds of $TT^*Q$…

Mathematical Physics · Physics 2018-03-14 O. Esen , M. de León , C. Sardón

We introduce the notion of Hamiltonian spaces for Manin pairs over manifolds, using the so-called generalized Dirac structures. As an example, we describe Hamiltonian spaces of a quasi-Lie bialgebroid using this general framework. We also…

Differential Geometry · Mathematics 2008-09-25 David Iglesias Ponte , Ping Xu

We construct so-called Darboux transformations and solutions of the dynamical Hamiltonian systems with several space variables $\frac{\partial \psi}{\partial t}=\sum_{k=1}^r H_k(t)\frac{\partial \psi}{\partial \zeta_k}\,$ $( H_k(t)=…

Dynamical Systems · Mathematics 2026-04-29 Alexander Sakhnovich

In this paper we derive the symplectic framework for field theories defined by higher-order Lagrangians. The construction is based on the symplectic reduction of suitable spaces of iterated jets. The possibility of reducing a higher-order…

Differential Geometry · Mathematics 2015-05-18 Jerzy Kijowski , Giovanni Moreno

The Lagrangians and dissipation functions are proposed for use in the electrodynamics of the double-negative and chiral metamaterials with finite loss. The double-negative metamaterial considered here is the wires and split rings periodic…

Classical Physics · Physics 2018-01-01 Pi-Gang Luan

We study the structure-preserving space discretization of port-Hamiltonian (pH) systems defined with differential constitutive relations. Using the concept of Stokes-Lagrange structure to describe these relations, these are reduced to a…

Numerical Analysis · Mathematics 2026-04-14 Antoine Bendimerad-Hohl , Ghislain Haine , Laurent Lefèvre , Denis Matignon

We introduce an equation named matrix Dirac equation which can be considered as a generalization of Dirac equation for an electron. The liaison between matrix Dirac equation and standard Dirac equation is discussed. We write a lagrangian…

Mathematical Physics · Physics 2007-05-23 N. G. Marchuk

A "minimal" generalization of Quantum Mechanics is proposed, where the Lagrangian or the action functional is a mapping from the (classical) states of a system to the Lie algebra of a general compact Lie group, and the wave function takes…

Quantum Physics · Physics 2007-05-23 Yu Tian

In this note we describe how some objects from generalized geometry appear in the qualitative analysis and numerical simulation of mechanical systems. In particular we discuss double vector bundles and Dirac structures. It turns out that…

Numerical Analysis · Mathematics 2018-07-19 Vladimir Salnikov , Aziz Hamdouni

We propose a generalization of Heisenberg picture quantum mechanics in which a Lagrangian and Hamiltonian dynamics is formulated directly for dynamical systems on a manifold with non--commuting coordinates, which act as operators on an…

High Energy Physics - Theory · Physics 2010-11-01 Stephen L. Adler

This work presents a general geometric framework for simulating and learning the dynamics of Hamiltonian systems that are invariant under a Lie group of transformations. This means that a group of symmetries is known to act on the system…

Mathematical Physics · Physics 2023-09-01 Miguel Vaquero , Jorge Cortés , David Martín de Diego

We analyze infinite-dimensional Hamiltonian systems corresponding to partial differential equations on one-dimensional spatial domains formulated with formally skew-adjoint Hamiltonian operators and nonlinear Hamiltonian density. In various…

Analysis of PDEs · Mathematics 2024-01-30 Till Preuster , Manuel Schaller , Bernhard Maschke

In this paper, we explore dynamics of the nonholonomic system called vakonomic mechanics in the context of Lagrange-Dirac dynamical systems using a Dirac structure and its associated Hamilton-Pontryagin variational principle. We first show…

Differential Geometry · Mathematics 2015-05-20 Fernando Jiménez , Hiroaki Yoshimura

We introduce the geometric structure underlying the port-Hamiltonian models for distributed parameter systems exhibiting moving material domains.

Analysis of PDEs · Mathematics 2022-03-14 Federico Califano , Ramy Rashad , Frederic P. Schuller , Stefano Stramigioli

The Lagrangian representation of multi-Hamiltonian PDEs has been introduced by Y. Nutku and one of us (MVP). In this paper we focus on systems which are (at least) bi-Hamiltonian by a pair $A_1$, $A_2$, where $A_1$ is a hydrodynamic-type…

Mathematical Physics · Physics 2017-01-31 M. V. Pavlov , R. F. Vitolo

Hydrogen's growing role in the transition towards climate-neutral energy systems necessitates structured modeling frameworks. Existing gas network models, largely developed for natural gas, fail to capture hydrogen systems distinct…

Optimization and Control · Mathematics 2025-12-03 Abdullah Shahin , Hannes Gernandt , Anton Plietzsch , Johannes Schiffer

Recent approaches for modelling dynamics of physical systems with neural networks enforce Lagrangian or Hamiltonian structure to improve prediction and generalization. However, when coordinates are embedded in high-dimensional data such as…

Machine Learning · Computer Science 2022-09-02 Yaofeng Desmond Zhong , Naomi Ehrich Leonard
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