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We present the mixed Galerkin discretization of distributed parameter port-Hamiltonian systems. On the prototypical example of hyperbolic systems of two conservation laws in arbitrary spatial dimension, we derive the main contributions: (i)…

Dynamical Systems · Mathematics 2018-03-02 Paul Kotyczka , Bernhard Maschke , Laurent Lefèvre

We consider the design of structure-preserving discretization methods for the solution of systems of boundary controlled Partial Differential Equations (PDEs) thanks to the port-Hamiltonian formalism. We first provide a novel general…

Numerical Analysis · Mathematics 2020-09-30 Andrea Brugnoli , Ghislain Haine , Anass Serhani , Xavier Vasseur

We discuss structure-preserving time discretization for nonlinear port-Hamiltonian systems with state-dependent mass matrix. Such systems occur, for instance, in the context of structure-preserving nonlinear model order reduction for…

Numerical Analysis · Mathematics 2023-11-02 Philipp Schulze

In this paper we propose a novel approach to discretize linear port-Hamiltonian systems while preserving the underlying structure. We present a finite element exterior calculus formulation that is able to mimetically represent conservation…

Numerical Analysis · Mathematics 2022-10-19 Andrea Brugnoli , Ramy Rashad , Stefano Stramigioli

A broad class of nonlinear acoustic wave models possess a Hamiltonian structure in their dissipation-free limit and a gradient flow structure for their dissipative dynamics. This structure may be exploited to design numerical methods which…

Numerical Analysis · Mathematics 2024-07-23 William Barham , Philip J. Morrison

Real physical systems are dissipative -- a pendulum slows, a circuit loses charge to heat -- and forecasting their dynamics from partial observations is a central challenge in scientific machine learning. We address the \emph{position-only}…

Machine Learning · Computer Science 2026-02-23 Shubham Bhardwaj , Chandrajit Bajaj

The discretization approximation method commonly used to simulate the dynamics of quantum system coupled to the environment in continuum often suffers from the periodically partial recovery of initial state because of the effect of finite…

Quantum Physics · Physics 2025-05-07 H. T. Cui , Y. A. Yan , M. Qin , X. X. Yi

For Hamiltonian systems, simulation algorithms that exactly conserve numerical energy or pseudo-energy have seen extensive investigation. Most available methods either require the iterative solution of nonlinear algebraic equations at each…

Numerical Analysis · Mathematics 2022-07-04 Stefan Bilbao , Michele Ducceschi , Fabiana Zama

In our earlier work [Fareed et al., Comput. Math. Appl. 75 (2018), no. 6, 1942-1960], we developed an incremental approach to compute the proper orthogonal decomposition (POD) of PDE simulation data. Specifically, we developed an…

Numerical Analysis · Mathematics 2021-02-01 Hiba Fareed , John R. Singler

We present a domain decomposition strategy for developing structure-preserving finite element discretizations from data when exact governing equations are unknown. On subdomains, trainable Whitney form elements are used to identify…

Numerical Analysis · Mathematics 2024-06-11 Shuai Jiang , Jonas Actor , Scott Roberts , Nathaniel Trask

We derive conditions under which a general nonlinear mechanical system can be exactly reduced to a lower-dimensional model that involves only the most flexible degrees of freedom. This Slow-Fast Decomposition (SFD) enslaves exponentially…

Dynamical Systems · Mathematics 2016-11-29 George Haller , Sten Ponsioen

In this work, we propose a new stochastic domain decomposition method for solving steady-state partial differential equations (PDEs) with random inputs. Based on the efficiency of the Variable-separation (VS) method in simulating stochastic…

Numerical Analysis · Mathematics 2025-02-06 Liang Chen , Yaru Chen , Qiuqi Li , Zhiwen Zhang

The modal analysis is revisited through the symplectic formalism, what leads to two intertwined eigenproblems. Studying the properties of the solutions, we prove that they form a canonical basis. The method is general and works even if the…

Model reduction using the proper orthogonal decomposition (POD) method is applied to the dynamics of ferroelastic patches to study the first order square to rectangular phase transformations. Governing equations for the system dynamics are…

Materials Science · Physics 2007-05-23 Linxiang X. Wang , Roderick V. N. Melnik

A key step in reverse engineering neural networks is to decompose them into simpler parts that can be studied in relative isolation. Linear parameter decomposition -- a framework that has been proposed to resolve several issues with current…

Machine Learning · Computer Science 2025-09-05 Lucius Bushnaq , Dan Braun , Lee Sharkey

Hamiltonian systems are differential equations which describe systems in classical mechanics, plasma physics, and sampling problems. They exhibit many structural properties, such as a lack of attractors and the presence of conservation…

Numerical Analysis · Mathematics 2022-01-14 Christian Offen , Sina Ober-Blöbaum

This article considers Hamiltonian mechanical systems with potential functions admitting jump discontinuities. The focus is on accurate and efficient numerical approximations of their solutions, which will be defined via the laws of…

Numerical Analysis · Mathematics 2022-01-05 Molei Tao , Shi Jin

We propose a new algorithm to compute a shifted proper orthogonal decomposition (sPOD) for systems dominated by multiple transport velocities. The sPOD is a recently proposed mode decomposition technique which overcomes the poor performance…

Numerical Analysis · Mathematics 2018-03-06 Philipp Schulze , Julius Reiss , Volker Mehrmann

Methods for discretizing port-Hamiltonian systems are of interest both for simulation and control purposes. Despite the large literature on mixed finite elements, no rigorous analysis of the connections between mixed elements and…

Numerical Analysis · Mathematics 2020-06-09 Andrea Brugnoli , Daniel Alazard , Valérie Pommier-Budinger , Denis Matignon

We introduce a new definition of discrete-time port-Hamiltonian systems (PHS), which results from structure-preserving discretization of explicit PHS in time. We discretize the underlying continuous-time Dirac structure with the collocation…

Dynamical Systems · Mathematics 2018-11-20 Paul Kotyczka , Laurent Lefèvre