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We give a systematic method for discretizing Hamiltonian partial differential equations (PDEs) with constant symplectic structure, while preserving their energy exactly. The same method, applied to PDEs with constant dissipative structure,…

Numerical Analysis · Mathematics 2015-06-04 E. Celledoni , V. Grimm , R. I. McLachlan , D. I. McLaren , D. O'Neale , B. Owren , G. R. W. Quispel

We develop a structure-preserving numerical discretization for the electrostatic Euler-Poisson equations with a constant magnetic field. The scheme preserves positivity of the density, positivity of the internal energy and a minimum…

Numerical Analysis · Mathematics 2025-10-15 Jordan Hoffart , Matthias Maier , John N. Shadid , Ignacio Tomas

The response of many materials to applied forces and boundary constraints depends upon internal geometric changes at multiple submacroscopic levels. Hierarchical structured deformations provide a mathematical setting for the description of…

Classical Analysis and ODEs · Mathematics 2025-05-15 Ana Cristina Barroso , José Matias , Marco Morandotti , David R. Owen , Elvira Zappale

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

The notion of dissipative dynamical systems provides a formal description of processes that cannot generate energy internally. For these systems, changes in energy can only occur due to an external energy supply or dissipation effects.…

Numerical Analysis · Mathematics 2026-02-18 Attila Karsai , Philipp Schulze

In this paper, we present a systematic framework to derive a Lagrangian scheme for porous medium type generalized diffusion equations by employing a discrete energetic variational approach. Such discrete energetic variational approaches are…

Numerical Analysis · Mathematics 2020-07-15 Chun Liu , Yiwei Wang

Mathematical descriptions of dynamical systems are deeply rooted in topological spaces defined by non-Euclidean geometry. This paper proposes leveraging structure-rich geometric spaces for machine learning to achieve structural…

Machine Learning · Computer Science 2025-02-20 Zack Xuereb Conti , David J Wagg , Nick Pepper

Given a set of inelastic material models, a microstructure, a macroscopic structural geometry, and a set of boundary conditions, one can in principle always solve the governing equations to determine the system's mechanical response.…

Computational Engineering, Finance, and Science · Computer Science 2023-06-27 Ghina Jezdan , Sanjay Govindjee , Klaus Hackl

Understanding the contact dynamics of nonspherical particles beyond the microscale is crucial for accurately modeling colloidal and granular systems, where shape anisotropy dictates structural organization and transport properties. In this…

Soft Condensed Matter · Physics 2026-03-06 Haoyuan Shi , Christopher J. Mundy , Gregory K. Schenter , Jaehun Chun

The parabolic-elliptic Keller-Segel equation with sensitivity saturation, because of its pattern formation ability, is a challenge for numerical simulations. We provide two finite-volume schemes whose goals are to preserve, at the discrete…

Numerical Analysis · Mathematics 2018-10-30 Luís Neves de Almeida , Federica Bubba , Benoît Perthame , Camille Pouchol

We present a finite element discretization of a non-linear diffusion equation used in the field of critical phenomena and, more recently, in the context of Dynamic Density Functional Theory. The discretized equation preserves the structure…

Statistical Mechanics · Physics 2015-06-23 J. A. de la Torre , Pep Español , Aleksandar Donev

In this paper we present a numerical method for hydrodynamic models that arise from time dependent density functional theories of freezing. The models take the form of compressible Navier-Stokes equations whose pressure is determined by the…

Numerical Analysis · Mathematics 2016-01-20 Arvind Baskaran , Zhen Guan , John Lowengrub

An energy-based model of the ferroelectric polarization process is presented in the current contribution. In an energy-based setting, dielectric displacement and strain (or displacement) are the primary independent unknowns. As an internal…

Numerical Analysis · Mathematics 2023-03-27 Astrid S. Pechstein , Martin Meindlhumer , Alexander Humer

Energy conserving particle-in-cell schemes are constructed for a class of reduced relativistic Vlasov--Maxwell equations of laser-plasma interaction. Discrete Poisson equation is also satisfied by the numerical solution. Specifically,…

Numerical Analysis · Mathematics 2022-11-30 Yingzhe Li

Learning the underlying potential energy of stochastic gradient systems from partial and noisy observations is a fundamental problem arising in physics, chemistry, and data-driven modeling. Classical approaches often rely on direct…

Machine Learning · Computer Science 2026-04-23 Yubin Lu , Xiaofan Li , Chun Liu , Qi Tang , Yiwei Wang

In this work, we aim to develop energy-stable parametric finite element approximations for a sharp-interface model with strong surface energy anisotropy, which is derived from the first variation of an energy functional composed of…

Numerical Analysis · Mathematics 2024-07-08 Meng Li , Chunjie Zhou

Numerical simulations of compressible real-fluid flows are notoriously plagued by spurious pressure oscillations arising in regions of abrupt flow variations. As a possible remedy, several numerical formulations enforce the pressure…

Fluid Dynamics · Physics 2026-05-27 Gennaro Coppola , Alessandro Aiello , Carlo De Michele

Energy-Based Models (EBMs) have proven to be a highly effective approach for modelling densities on finite-dimensional spaces. Their ability to incorporate domain-specific choices and constraints into the structure of the model through…

Machine Learning · Computer Science 2023-02-24 Jen Ning Lim , Sebastian Vollmer , Lorenz Wolf , Andrew Duncan

It is proposed that the mathematical models for any physical systems that are based in first principles, such as conservation laws or balance principles, have some common elements, namely, a space of kinematical states, a space of dynamical…

Mathematical Physics · Physics 2015-06-03 D. H. Delphenich

We extend the theory of structured deformations to the setting of linearized elasticity by providing an integral representation for the underlying energy that features bulk and surface contributions. Our derivation is obtained both via a…

Analysis of PDEs · Mathematics 2026-01-19 Manuel Friedrich , José Matias , Elvira Zappale
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