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This paper is concerned with the relationship between the discrete and the continuous decreasing minimization problem on base-polyhedra. The continuous version (under the name of lexicographically optimal base of a polymatroid) was solved…

Combinatorics · Mathematics 2022-04-13 András Frank , Kazuo Murota

Some positive answers to the problem of endowing a dynamical system with a Hamiltonian formulation are presented within the class of Poisson structures in a geometric framework. We address this problem on orientable manifolds and by using…

We continue to consider the discrete decreasing minimization problem on an integral base-polyhedron treated in Part I. The problem is to find a lexicographically minimal integral vector in an integral base-polyhedron, where the components…

Combinatorics · Mathematics 2020-07-01 András Frank , Kazuo Murota

This work focuses on the development of a non-conforming domain decomposition method for the approximation of PDEs based on weakly imposed transmission conditions: the continuity of the global solution is enforced by a discrete number of…

Numerical Analysis · Mathematics 2018-03-06 Simone Deparis , Luca Pegolotti

A finite element methodology for large classes of variational boundary value problems is defined which involves discretizing two linear operators: (1) the differential operator defining the spatial boundary value problem; and (2) a Riesz…

Numerical Analysis · Mathematics 2017-12-08 Brendan Keith , Socratis Petrides , Federico Fuentes , Leszek Demkowicz

In these notes, we present an alternative version of discrete Dirac mechanics using Dirac structures. We first establish a notion of 'continuous Dirac system' and then propose a definition of discrete Dirac system, proving that it is…

Differential Geometry · Mathematics 2024-08-19 Matías I. Caruso , Javier Fernández , Cora Tori , Marcela Zuccalli

The Poisson structures for 3D systems possessing one constant of motion can always be constructed from the solution of a linear PDE. When two constants of the motion are available the problem reduces to a quadrature and the structure…

Mathematical Physics · Physics 2009-11-07 F. Haas , J. Goedert

We present a new technique to apply finite element methods to partial differential equations over curved domains. A change of variables along a coordinate transformation satisfying only low regularity assumptions can translate a Poisson…

Numerical Analysis · Mathematics 2018-09-28 M. Holst , M. Licht

This paper is concerned with approximations and related discretization error estimates for the normal derivatives of solutions of linear elliptic partial differential equations. In order to illustrate the ideas, we consider the Poisson…

Numerical Analysis · Mathematics 2018-04-17 J. Pfefferer , M. Winkler

The recent interest in structure preserving stochastic Lagrangian and Hamiltonian systems raises questions regarding how such models are to be understood and the principles through which they are to be derived. By considering a…

Mathematical Physics · Physics 2024-11-20 Oliver D. Street , So Takao

We show that any second order linear ordinary diffrential equation with constant coefficients (including the damped and undumped harmonic oscillator equation) admits an exact discretization, i.e., there exists a difference equation whose…

Popular Physics · Physics 2007-05-23 Jan L. Cieslinski , Boguslaw Ratkiewicz

The proximal Galerkin finite element method is a high-order, low-iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of point-wise bound constraints in infinite-dimensional function spaces.…

Numerical Analysis · Mathematics 2024-12-18 Brendan Keith , Thomas M. Surowiec

We extend the modeling framework of port-Hamiltonian descriptor systems to include under- and over-determined systems and arbitrary differentiable Hamiltonian functions. This structure is associated with a Dirac structure that encloses its…

Optimization and Control · Mathematics 2019-03-26 Volker Mehrmann , Riccardo Morandin

We consider the integral definition of the fractional Laplacian and analyze a linear-quadratic optimal control problem for the so-called fractional heat equation; control constraints are also considered. We derive existence and uniqueness…

Optimization and Control · Mathematics 2020-06-24 Christian Glusa , Enrique Otarola

This article considers a model problem of elastoplasticity with linearly kinematic hardening and presents hp-finite element discretizations of two equivalent weak formulations each having their respective advantages. A mixed variational…

Numerical Analysis · Mathematics 2026-05-12 Patrick Bammer , Lothar Banz , Miriam Schönauer , Andreas Schröder

A low-order nonconforming finite element discretization of a smooth de Rham complex starting from the $H^2$ space in three dimensions is proposed, involving an $H^2$-nonconforming finite element space, a new tangentially continuous…

Numerical Analysis · Mathematics 2025-12-05 Xuewei Cui , Xuehai Huang

In multi-phase fluid flow, fluid-structure interaction, and other applications, partial differential equations (PDEs) often arise with discontinuous coefficients and singular sources (e.g., Dirac delta functions). These complexities arise…

Numerical Analysis · Mathematics 2019-07-24 Chung-Nan Tzou , Samuel Stechmann

In this paper higher order mimetic discretizations are introduced which are firmly rooted in the geometry in which the variables are defined. The paper shows how basic constructs in differential geometry have a discrete counterpart in…

Numerical Analysis · Mathematics 2011-11-21 Jasper Kreeft , Artur Palha , Marc Gerritsma

Respecting the laws of thermodynamics is crucial for ensuring that numerical simulations of dynamical systems deliver physically relevant results. In this paper, we construct a structure-preserving and thermodynamically consistent finite…

Numerical Analysis · Mathematics 2024-09-23 Evan S. Gawlik , François Gay-Balmaz

The article introduces a method to learn dynamical systems that are governed by Euler--Lagrange equations from data. The method is based on Gaussian process regression and identifies continuous or discrete Lagrangians and is, therefore,…

Numerical Analysis · Mathematics 2025-07-01 Christian Offen
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