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In this work, we introduce implicit Finite Operator Learning (iFOL) for the continuous and parametric solution of partial differential equations (PDEs) on arbitrary geometries. We propose a physics-informed encoder-decoder network to…

Machine Learning · Computer Science 2025-12-09 Reza Najian Asl , Yusuke Yamazaki , Kianoosh Taghikhani , Mayu Muramatsu , Markus Apel , Shahed Rezaei

We present a novel implicit scheme for the numerical solution of time-dependent conservation laws. The core idea of the presented method is to exploit and approximate the mixed spatial-temporal derivative of the solution that occurs…

Numerical Analysis · Mathematics 2022-12-13 Peter Frolkovič , Michal Žeravý

This work discusses the model reduction problem for large-scale multi-symplectic PDEs with cubic invariants. For this, we present a linearly implicit global energy-preserving method to construct reduced-order models. This allows to…

Numerical Analysis · Mathematics 2023-08-08 Süleyman Yildiz , Pawan Goyal , Peter Benner

This paper presents a numerical method for variable coefficient elliptic PDEs with mostly smooth solutions on two dimensional domains. The PDE is discretized via a multi-domain spectral collocation method of high local order (order 30 and…

Numerical Analysis · Mathematics 2016-12-09 Tracy Babb , Adrianna Gillman , Sijia Hao , Per-Gunnar Martinsson

We present a modified version of the PRESB preconditioner for two-by-two block system of linear equations with the coefficient matrix $$\textbf{A}=\left(\begin{array}{cc} F & -G^* G & F \end{array}\right),$$ where $F\in\mathbb{C}^{n\times…

Numerical Analysis · Mathematics 2024-05-15 Owe Axelsson , Dovod Khojasteh Slakuyeh

The material point method (MPM) has been increasingly used for the simulation of large deformation processes in fluid-infiltrated porous materials. For undrained poromechanical problems, however, standard MPMs are numerically unstable…

Numerical Analysis · Mathematics 2020-02-27 Yidong Zhao , Jinhyun Choo

This paper provides the first provable $\mathcal{O}(N \log N)$ algorithms for the linear system arising from the direct finite element discretization of the fourth-order equation with different boundary conditions on unstructured grids of…

Numerical Analysis · Mathematics 2012-03-06 Shuo Zhang , Jinchao Xu

A new preconditioner based on a block $LDU$ factorization with algebraic multigrid subsolves for scalability is introduced for the large, structured systems appearing in implicit Runge-Kutta time integration of parabolic partial…

Numerical Analysis · Mathematics 2021-01-15 Md Masud Rana , Victoria E. Howle , Katharine Long , Ashley Meek , William Milestone

This paper presents a structure-preserving spatial discretization method for distributed parameter port-Hamiltonian systems. The class of considered systems are hyperbolic systems of two conservation laws in arbitrary spatial dimension and…

Numerical Analysis · Mathematics 2021-08-11 Flávio Luiz Cardoso-Ribeiro , Denis Matignon , Laurent Lefèvre

A numerical analysis for the fully discrete approximation of an operator Lyapunov equation related to linear SPDEs (stochastic partial differential equations) driven by multiplicative noise is considered. The discretization of the Lyapunov…

Numerical Analysis · Mathematics 2022-05-04 Adam Andersson , Annika Lang , Andreas Petersson , Leander Schroer

Electroactive polymers such as dielectric elastomers (DEs) have attracted significant attention in recent years. Computational techniques to solve the coupled electromechanical system of equations for this class of materials have…

Computational Physics · Physics 2018-04-03 Saman Seifi , K. C. Park , Harold S. Park

First-order fully implicit as well as implicit--explicit schemes for coupled elliptic-parabolic systems are discussed in [Ern and Meunier, ESAIM: M2AN, 2009] and [Altmann et al., Math.\ Comp., 2021], respectively. The extension of the…

Numerical Analysis · Mathematics 2026-01-06 Georgios Akrivis , Minghua Chen , Fan Yu

In this paper, we develop two classes of robust preconditioners for the structure-preserving discretization of the incompressible magnetohydrodynamics (MHD) system. By studying the well-posedness of the discrete system, we design block…

Numerical Analysis · Mathematics 2016-06-22 Yicong Ma , Kaibo Hu , Xiaozhe Hu , Jinchao Xu

In this article we derive a priori error estimates for the $hp$-version of the mortar finite element method for parabolic initial-boundary value problems. Both semidiscrete and fully discrete methods are analysed in $L^2$- and $H^1$-norms.…

Analysis of PDEs · Mathematics 2018-07-24 Sanjib Kumar Acharya , Ajit Patel , Talal Rahman

Simulating complex physical systems is crucial for understanding and predicting phenomena across diverse fields, such as fluid dynamics and heat transfer, as well as plasma physics and structural mechanics. Traditional approaches rely on…

A lesser-known but powerful application of parabolic equation methods is to the target scattering problem. In this paper, we use noncanonically shaped objects to establish the limits of applicability of the traditional approach, and…

Computational Physics · Physics 2020-01-29 Adith Ramamurti , David C. Calvo

Finite element simulations have been used to solve various partial differential equations (PDEs) that model physical, chemical, and biological phenomena. The resulting discretized solutions to PDEs often do not satisfy requisite physical…

Numerical Analysis · Mathematics 2022-03-17 Vidhi Zala , Robert M. Kirby , Akil Narayan

We present new, practical algorithms for the hypersurface implicitization problem: namely, given a parametric description (in terms of polynomials or rational functions) of the hypersurface, find its implicit equation. Two of them are for…

Commutative Algebra · Mathematics 2016-10-14 John Abbott , Anna Maria Bigatti , Lorenzo Robbiano

Mechanistic knowledge about the physical world is virtually always expressed via partial differential equations (PDEs). Recently, there has been a surge of interest in probabilistic PDE solvers -- Bayesian statistical models mostly based on…

Machine Learning · Computer Science 2025-03-12 Tim Weiland , Marvin Pförtner , Philipp Hennig

The quasi-neutral hybrid model with kinetic ions and fluid electrons is a promising approach for bridging the inherent multi-scale nature of many problems in space and laboratory plasmas. Here, a novel, implicit, particle-in-cell based…

Plasma Physics · Physics 2018-11-14 A. Stanier , L. Chacón , G. Chen
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