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We study the optimal design of numerical integrators for dissipative systems, for which there exists an underlying thermodynamic structure known as GENERIC (general equation for the nonequilibrium reversible-irreversible coupling). We…

Numerical Analysis · Mathematics 2020-02-14 Xiaocheng Shang , Hans Christian Öttinger

In a recent series of papers, the class of energy-conserving Runge-Kutta methods named Hamiltonian BVMs (HBVMs) has been defined and studied. Such methods have been further generalized for the efficient solution of general conservative…

Numerical Analysis · Mathematics 2014-03-05 Luigi Brugnano , Yajuan Sun

We use the general framework of summation-by-parts operators to construct conservative, energy-stable, and well-balanced semidiscretizations of two different nonlinear systems of dispersive shallow water equations with varying bathymetry:…

Numerical Analysis · Mathematics 2025-11-12 Joshua Lampert , Hendrik Ranocha

Biological and physical systems often exhibit distinct structures at different spatial/temporal scales. Persistent homology is an algebraic tool that provides a mathematical framework for analyzing the multi-scale structures frequently…

Algebraic Topology · Mathematics 2016-02-01 Jonathan Jaquette , Miroslav Kramár

In this work we consider an extension of a recently proposed structure preserving numerical scheme for nonlinear Fokker-Planck-type equations to the case of nonconstant full diffusion matrices. While in existing works the schemes are…

Numerical Analysis · Mathematics 2021-04-20 N. Loy , M. Zanella

Recently, the class of energy-conserving Runge-Kutta methods named Hamiltonian Boundary Value Methods (HBVMs), has been proposed for the efficient solution of Hamiltonian problems, as well as for other types of conservative problems. In…

Numerical Analysis · Mathematics 2013-10-22 Luigi Brugnano , Yajuan Sun

This study proposes a high-order multi-scale method tailored for time-dependent nonlinear thermo-electro-mechanical coupling problems of composite structures with highly spatial heterogeneity, which incorporate temperature-dependent…

Numerical Analysis · Mathematics 2026-04-22 Hao Dong

Impulse methods are generalized to a family of integrators for Langevin systems with quadratic stiff potentials and arbitrary soft potentials. Uniform error bounds (independent from stiff parameters) are obtained on integrated positions…

Numerical Analysis · Mathematics 2010-06-25 Molei Tao , Houman Owhadi , Jerrold E. Marsden

Large-scale quantum devices provide insights beyond the reach of classical simulations. However, for a reliable and verifiable quantum simulation, the building blocks of the quantum device require exquisite benchmarking. This benchmarking…

Quantum Physics · Physics 2022-02-16 Agnes Valenti , Guliuxin Jin , Julian Léonard , Sebastian D. Huber , Eliska Greplova

Most numerical integration algorithms are not designed specifically for Hamiltonian systems and do not respect their characteristic properties, which include the preservation of phase space volume with time. This can lead to spurious…

Astrophysics · Physics 2015-06-24 David JD Earn

It is well-known that a numerical method which is at the same time geometric structure-preserving and physical property-preserving cannot exist in general for Hamiltonian partial differential equations. In this paper, we present a novel…

Numerical Analysis · Mathematics 2019-07-25 Chuchu Chen , Jialin Hong , Chol Sim , Kwang Sonwu

We consider multiscale Hamiltonian systems in which harmonic oscillators with several high frequencies are coupled to a slow system. It is shown that the oscillatory energy is nearly preserved over long times eps^{-N} for arbitrary N>1,…

Dynamical Systems · Mathematics 2015-06-05 Ludwig Gauckler , Ernst Hairer , Christian Lubich

We consider several Hamiltonian systems perturbed by external agents, that preserve their Hamiltonian structure. We investigate the corrections to the canonical statistics resulting from coupling such systems with possibly large but finite…

Statistical Mechanics · Physics 2023-05-25 Matteo Colangeli , Antonio Di Francesco , Lamberto Rondoni

Hamilton's equations are fundamental for modeling complex physical systems, where preserving key properties such as energy and momentum is crucial for reliable long-term simulations. Geometric integrators are widely used for this purpose,…

Machine Learning · Computer Science 2026-03-17 Priscilla Canizares , Davide Murari , Carola-Bibiane Schönlieb , Ferdia Sherry , Zakhar Shumaylov

In this article, we present a numerical approach to ensure the preservation of physical bounds on the solutions to linear and nonlinear hyperbolic convection-reaction problems at the discrete level. We provide a rigorous framework for error…

Numerical Analysis · Mathematics 2025-01-22 Ben S. Ashby , Abdalaziz Hamdan , Tristan Pryer

Machine learning methods are widely used in the natural sciences to model and predict physical systems from observation data. Yet, they are often used as poorly understood "black boxes," disregarding existing mathematical structure and…

Machine Learning · Computer Science 2023-10-24 Marco David , Florian Méhats

We introduce a nonlinear structure preserving high-order scheme for anisotropic advection-diffusion equations. This scheme, based on Hybrid High-Order methods, can handle general meshes. It also has an entropy structure, and preserves the…

Numerical Analysis · Mathematics 2023-10-20 Julien Moatti

One main issue, when numerically integrating autonomous Hamiltonian systems, is the long-term conservation of some of its invariants, among which the Hamiltonian function itself. Recently, a new class of methods, named Hamiltonian Boundary…

Numerical Analysis · Mathematics 2010-02-24 Luigi Brugnano , Felice Iavernaro , Donato Trigiante

Periodic dynamical systems ubiquitously exist in science and engineering. The harmonic balance (HB) method and its variants have been the most widely-used approaches for such systems, but are either confined to low-order approximations or…

Numerical Analysis · Mathematics 2022-03-15 Honghua Dai , Zipu Yan , Xuechuan Wang , Xiaokui Yue , Satya N. Atluri

A framework for identifying nonlinear port-Hamiltonian systems using input-state-output data is introduced. The framework utilizes neural networks' universal approximation capacity to effectively represent complex dynamics in a structured…

Systems and Control · Electrical Eng. & Systems 2025-02-18 Karim Cherifi , Achraf El Messaoudi , Hannes Gernandt , Marco Roschkowski