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One- and multi-dimensional stochastic Maxwell equations with additive noise are considered in this paper. It is known that such system can be written in the multi-symplectic structure, and the stochastic energy increases linearly in time.…

Numerical Analysis · Mathematics 2022-05-04 Jiawei Sun , Chi-Wang Shu , Yulong Xing

Over the last few years there have been dramatic advances in our understanding of mathematical and computational models of complex systems in the presence of uncertainty. This has led to a growth in the area of uncertainty quantification as…

Numerical Analysis · Mathematics 2013-06-04 Maziar Raissi , Padmanabhan Seshaiyer

We introduce a filtering technique for Discontinuous Galerkin approximations of hyperbolic problems. Following an approach already proposed for the Hamilton-Jacobi equations by other authors, we aim at reducing the spurious oscillations…

Numerical Analysis · Mathematics 2023-05-18 Giuseppe Orlando

We present a new structure-preserving model order reduction (MOR) framework for large-scale port-Hamiltonian descriptor systems (pH-DAEs). Our method exploits the structural properties of the Rosenbrock system matrix for this system class…

Systems and Control · Electrical Eng. & Systems 2022-10-31 Tim Moser , Boris Lohmann

In this contribution, we introduce a general class of car-following models with an input-state-output port-Hamiltonian structure. We derive stability conditions and long-term behavior of the finite system with periodic boundaries and…

Dynamical Systems · Mathematics 2025-02-04 Julia Ackermann , Matthias Ehrhardt , Thomas Kruse , Antoine Tordeux

We investigate numerical behaviour of a convection diffusion equation with random coefficients by approximating statistical moments of the solution. Stochastic Galerkin approach, turning the original stochastic problem to a system of…

Numerical Analysis · Mathematics 2021-10-19 Pelin Çiloğlu , Hamdullah Yücel

Port-Hamiltonian systems are pertinent representations of many nonlinear physical systems. In this study, we formulate and analyse a general class of stochastic car-following models with a systematic port-Hamiltonian structure. The model…

Dynamical Systems · Mathematics 2024-06-12 Barbara Rüdiger , Antoine Tordeux , Baris Ugurcan

Variational integrators are derived for structure-preserving simulation of stochastic Hamiltonian systems with a certain type of multiplicative noise arising in geometric mechanics. The derivation is based on a stochastic discrete…

Numerical Analysis · Mathematics 2019-07-31 Darryl D. Holm , Tomasz M. Tyranowski

It is a universal phenomenon that the state and input of the continuous stirred tank reactor (CSTR) systems are both disturbed. This paper proposes a (state, input)-disturbed port-Hamiltonian framework that can be used to model and further…

Optimization and Control · Mathematics 2017-07-07 Yafei Lu , Zhou Fang , Chuanhou Gao

Numerical methods for stochastic partial differential equations typically estimate moments of the solution from sampled paths. Instead, we shall directly target the deterministic equations satisfied by the first and second moments, as well…

Numerical Analysis · Mathematics 2020-11-17 Kristin Kirchner

In this paper, we develop a class of high order conservative semi-Lagrangian (SL) discontinuous Galerkin (DG) methods for solving multi-dimensional linear transport equations. The methods rely on a characteristic Galerkin weak formulation,…

Numerical Analysis · Mathematics 2017-09-25 Xiaofeng Cai , Wei Guo , Jing-Mei Qiu

In this work, we present a discontinuous-Galerkin method for evolving relativistic hydrodynamics. We include an exploration of analytical and iterative methods to recover the primitive variables from the conserved variables for the ideal…

A general framework for the numerical approximation of evolution problems is presented that allows to preserve exactly an underlying Hamiltonian- or gradient structure. The approach relies on rewriting the evolution problem in a particular…

Numerical Analysis · Mathematics 2018-12-12 Herbert Egger

In this paper we study the finite element approximation of systems of second-order nonlinear hyperbolic equations. The proposed numerical method combines a $hp$-version discontinuous Galerkin finite element approximation in the time…

Numerical Analysis · Mathematics 2022-12-02 Aili Shao

A structure preserving proper orthogonal decomposition reduce-order modeling approach has been developed in [Gong et al. 2017] for the Hamiltonian system, which uses the traditional framework of Galerkin projection-based model reduction but…

Numerical Analysis · Mathematics 2021-03-03 Zhu Wang

In this contribution, we extend the hybridization framework for the Hodge Laplacian [Awanou et al., Hybridization and postprocessing in finite element exterior calculus, 2023] to port-Hamiltonian systems describing linear wave propagation…

Numerical Analysis · Mathematics 2025-02-25 Andrea Brugnoli , Ramy Rashad , Yi Zhang , Stefano Stramigioli

We consider a space-time variational formulation of the second-order wave equation, where integration by parts is also applied with respect to the time variable. Conforming tensor-product finite element discretisations with piecewise…

Numerical Analysis · Mathematics 2021-02-16 Marco Zank

We develop a hybrid spatial discretization for the wave equation in second order form, based on high-order accurate finite difference methods and discontinuous Galerkin methods. The hybridization combines computational efficiency of finite…

Numerical Analysis · Mathematics 2022-10-26 Siyang Wang , Gunilla Kreiss

It is shown analytically that the energy-conserving implicit nonsymplectic scheme of Bacchini, Ripperda, Chen and Sironi provides a first-order accuracy to numerical solutions of a six-dimensional conservative Hamiltonian system. Because of…

General Relativity and Quantum Cosmology · Physics 2021-12-08 Shiyang Hu , Xin Wu , Enwei Liang

An important class of spatio-temporal models is constructed by leveraging the hierarchical structure of dynamical (or, state-space) models. This paper proposes a new statistical dynamical model for spatio-temporal processes motivated by…

Methodology · Statistics 2026-05-11 Yutong Zhang , Xiao Liu