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In the discretization of differential problems on complex geometrical domains, discretization methods based on polygonal and polyhedral elements are powerful tools. Adaptive mesh refinement for such kind of problems is very useful as well…

Numerical Analysis · Mathematics 2019-12-12 Stefano Berrone , Andrea Borio , Alessandro D'Auria

In a recent work [10], we have introduced a pressure-robust Hybrid High-Order method for the numerical solution of the incompressible Navier-Stokes equations on matching simplicial meshes. Pressure-robust methods are characterized by error…

Numerical Analysis · Mathematics 2026-01-22 Daniel Castanon Quiroz , Daniele A. Di Pietro

We present a novel Hybrid High-Order (HHO) discretization of fourth-order elliptic problems arising from the mechanical modeling of the bending behavior of Kirchhoff-Love plates, including the biharmonic equation as a particular case. The…

Numerical Analysis · Mathematics 2018-01-25 Francesco Bonaldi , Daniele A. Di Pietro , Giuseppe Geymonat , Françoise Krasucki

This paper provides a rigorous analysis of boundary element methods for the magnetic field integral equation on Lipschitz polyhedra. The magnetic field integral equation is widely used in practical applications to model electromagnetic…

Numerical Analysis · Mathematics 2024-09-12 Van Chien Le , Kristof Cools

We present a computationally efficient approach to solve the time-dependent Kohn-Sham equations in real-time using higher-order finite-element spatial discretization, applicable to both pseudopotential and all-electron calculations. To this…

Computational Physics · Physics 2019-10-02 Bikash Kanungo , Vikram Gavini

Obtainable computational efficiency is evaluated when using an Adaptive Mesh Refinement (AMR) strategy in time accurate simulations governed by sets of conservation laws. For a variety of 1D, 2D, and 3D hydro- and magnetohydrodynamic…

Astrophysics · Physics 2009-11-10 R. Keppens , M. Nool , G. Toth , J. P. Goedbloed

In this work we explore the fidelity of numerical approximations to the analytic spectra of hyperbolic partial differential equation systems with variable coefficients. We are particularly interested in the ability of discrete methods to…

Numerical Analysis · Mathematics 2025-08-12 Brittany A. Erickson

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

We devise and analyze hybrid polyhedral methods of arbitrary order for the approximation of div-curl systems on three-dimensional domains featuring non-trivial topology. The div-curl systems we are interested in stem from magnetostatics,…

Numerical Analysis · Mathematics 2025-06-25 Jérémy Dalphin , Jean-Pierre Ducreux , Simon Lemaire , Silvano Pitassi

In this work, we propose a high-order multiscale method for an elliptic model problem with rough and possibly highly oscillatory coefficients. Convergence rates of higher order are obtained using the regularity of the right-hand side only.…

Numerical Analysis · Mathematics 2023-04-18 Zhaonan Dong , Moritz Hauck , Roland Maier

We present a Finite Volume formulation for determining discontinuous distributions of magnetic fields within non-orthogonal and non-uniform meshes. The numerical approach is based on the discretization of the vector potential variant of the…

Numerical Analysis · Mathematics 2024-08-13 Augusto Riedinger , Martín Saravia , José Ramírez

Particle-based methods are a practical tool in computational fluid dynamics, and novel types of methods have been proposed. However, widely developed Lagrangian-type formulations suffer from the nonuniform distribution of particles, which…

Fluid Dynamics · Physics 2025-03-26 Takeharu Matsuda , Satoshi Ii

High-order methods for convex and nonconvex optimization, particularly $p$th-order Adaptive Regularization Methods (AR$p$), have attracted significant research interest by naturally incorporating high-order Taylor models into adaptive…

Optimization and Control · Mathematics 2025-04-30 Wenqi Zhu , Coralia Cartis

We examine the challenges associated with numerical integration when applying Neural Networks to solve Partial Differential Equations (PDEs). We specifically investigate the Deep Ritz Method (DRM), chosen for its practical applicability and…

Numerical Analysis · Mathematics 2025-05-09 Jamie M. Taylor , David Pardo

Mathematical descriptions of flow phenomena usually come in the form of partial differential equations. The differential operators used in these equations may have properties such as symmetry, skew-symmetry, positive or negative…

Numerical Analysis · Mathematics 2017-10-20 Bas van 't Hof , Mathea J. Vuik

A discretisation of differential geometry using the Whitney forms of algebraic topology is consistently extended via the introduction of a pairing on the space of chains. This pairing of chains enables us to give a definition of the…

High Energy Physics - Theory · Physics 2007-05-23 Vivien de Beauce , Siddhartha Sen

We present a higher-order extension of the dual cell method for the time-domain Maxwell equations in three spatial dimensions. The approach builds upon a variational reinterpretation of the Finite Integration Technique on dual meshes and…

Numerical Analysis · Mathematics 2026-04-16 Lorenzo Codecasa , Bernard Kapidani , Joachim Schöberl , Markus Wess

This article presents a new high-order accurate algorithm for finding a particular solution to a linear, constant-coefficient partial differential equation (PDE) by means of a convolution of the volumetric source function with the Green's…

Numerical Analysis · Mathematics 2022-10-20 Thomas G. Anderson , Hai Zhu , Shravan Veerapaneni

In mixed finite element approximations of Hodge Laplace problems associated with the de Rham complex, the exterior derivative operators are computed exactly, so the spatial locality is preserved. However, the numerical approximations of the…

Numerical Analysis · Mathematics 2019-10-30 Jeonghun J. Lee

Models incorporating uncertain inputs, such as random forces or material parameters, have been of increasing interest in PDE-constrained optimization. In this paper, we focus on the efficient numerical minimization of a convex and smooth…

Optimization and Control · Mathematics 2021-06-18 Caroline Geiersbach , Winnifried Wollner
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