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Domain decomposition (DD) methods are widely used as preconditioner techniques. Their effectiveness relies on the choice of a locally constructed coarse space. Thus far, this construction was mostly achieved using non-assembled matrices…

Numerical Analysis · Mathematics 2021-09-14 Hussam Al Daas , Pierre Jolivet

Isogeometric analysis uses the same class of basis functions for both, representing the geometry of the computational domain and approximating the solution. In practical applications, geometrical patches are used in order to get flexibility…

Numerical Analysis · Mathematics 2014-02-11 Ulrich Langer , Stephen Edward Moore

We propose a multiscale method for mixed-dimensional elliptic problems with highly heterogeneous coefficients arising, for example, in the modeling of fractured porous media. The method is based on the Localized Orthogonal Decomposition…

Numerical Analysis · Mathematics 2026-03-23 Moritz Hauck , Axel Målqvist , Malin Mosquera

Realistic physical phenomena exhibit random fluctuations across many scales in the input and output processes. Models of these phenomena require stochastic PDEs. For three-dimensional coupled (vector-valued) stochastic PDEs (SPDEs), for…

Computational Engineering, Finance, and Science · Computer Science 2022-08-24 Ajit Desai , Mohammad Khalil , Chris L. Pettit , Dominique Poirel , Abhijit Sarkar

In this paper a discretization based on discontinuous Galerkin (DG) method for an elliptic two-dimensional problem with discontinuous coefficients is considered. The problem is posed on a polygonal region $\Omega$ which is a union of $N$…

Numerical Analysis · Mathematics 2014-01-07 Maksymilian Dryja , Juan Galvis , Marcus Sarkis

Coarse spaces are essential to ensure robustness w.r.t. the number of subdomains in two-level overlapping Schwarz methods. Robustness with respect to the coefficients of the underlying partial differential equation (PDE) can be achieved by…

Numerical Analysis · Mathematics 2025-10-31 Peter Bastian , Nils Friess

Scaling up quantum computers to attain substantial speedups over classical computing requires fault tolerance. Conventionally, protocols for fault-tolerant quantum computation demand excessive space overheads by using many physical qubits…

Quantum Physics · Physics 2025-01-29 Hayata Yamasaki , Masato Koashi

We study Hibridizable Discontinuous Galerkin (HDG) discretizations for a class of non-linear interior elliptic boundary value problems posed in curved domains where both the source term and the diffusion coefficient are non-linear. We…

Numerical Analysis · Mathematics 2021-12-30 Nestor Sánchez , Tonatiuh Sánchez-Vizuet , Manuel E. Solano

In this work, we develop algebraic solvers for linear systems arising from the discretization of second-order elliptic partial differential equations by saddle-point mixed finite element methods of arbitrary polynomial degree $p \ge 0$ on…

Numerical Analysis · Mathematics 2026-02-03 Ani Miraçi , Jan Papež , Martin Vohralík , Ivan Yotov

This paper proposes a domain decomposition subspace neural network method for efficiently solving linear and nonlinear partial differential equations. By combining the principles of domain decomposition and subspace neural networks, the…

Numerical Analysis · Mathematics 2025-05-28 Zhenxing Fu , Hongliang Liu , Zhiqiang Sheng , Baixue Xing

In this paper, we are interested in scalable Domain Decomposition Methods (DDM). To this end, we introduce and study a new Coarse Space Correction algorithm for Optimized Schwarz Methods(OSM) : the DCS-DGLC algorithm. The main idea is to…

Numerical Analysis · Mathematics 2013-10-01 Kévin Santugini-Repiquet

A local weighted discontinuous Galerkin gradient discretization method for solving elliptic equations is introduced. The local scheme is based on a coarse grid and successively improves the solution solving a sequence of local elliptic…

Numerical Analysis · Mathematics 2018-07-30 Assyr Abdulle , Giacomo Rosilho de Souza

This paper presents four novel domain decomposition algorithms integrated with nonlinear mapping techniques to address collocation-based solutions of eigenvalue problems involving sharp interfaces or steep gradients. The proposed methods…

Numerical Analysis · Mathematics 2025-02-14 Jinwei Yang , Vinod Srinivasan

A new decomposition optimization algorithm, called \textit{path-following gradient-based decomposition}, is proposed to solve separable convex optimization problems. Unlike path-following Newton methods considered in the literature, this…

Optimization and Control · Mathematics 2012-09-21 Quoc Tran Dinh , Ion Necoara , Moritz Diehl

In this paper we propose a variant of the substructuring preconditioner for solving three-dimensional elliptic-type equations with strongly discontinuous coefficients. In the proposed preconditioner, we use the simplest coarse solver…

Numerical Analysis · Mathematics 2018-01-15 Qiya Hu , Shaoliang Hu

Linear systems with large differences between coefficients ("discontinuous coefficients") arise in many cases in which partial differential equations(PDEs) model physical phenomena involving heterogeneous media. The standard approach to…

Mathematical Software · Computer Science 2009-05-04 Dan Gordon , Rachel Gordon

In this paper we design, analyse and test domain decomposition methods for linear systems of equations arising from conforming finite element discretisations of positive Maxwell-type equations, namely for $\mathbf{H}(\mathbf{curl})$…

Numerical Analysis · Mathematics 2025-10-28 Niall Bootland , Victorita Dolean , Frédéric Nataf , Pierre-Henri Tournier

We propose two variants of the overlapping additive Schwarz method for the finite element discretiza- tion of the elliptic problem in 3D with highly heterogeneous coefficients. The methods are efficient and simple to construct using the…

Numerical Analysis · Mathematics 2016-11-04 Erik Eikeland , Leszek Marcinkowski , Talal Rahman

An abstract framework for constructing stable decompositions of the spaces corresponding to general symmetric positive definite problems into "local" subspaces and a global "coarse" space is developed. Particular applications of this…

Numerical Analysis · Mathematics 2011-05-06 Y. Efendiev , J. Galvis , R. Lazarov , J. Willems

A novel domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) model-reduction method applicable to parameterized systems of nonlinear algebraic equations (e.g., arising from discretizing a parameterized partial-differential-equations…

Numerical Analysis · Mathematics 2021-07-07 Chi Hoang , Youngsoo Choi , Kevin Carlberg