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Agglomeration-based strategies are important both within adaptive refinement algorithms and to construct scalable multilevel algebraic solvers. In order to automatically perform agglomeration of polygonal grids, we propose the use of…

Numerical Analysis · Mathematics 2023-03-17 P. F. Antonietti , N. Farenga , E. Manuzzi , G. Martinelli , L. Saverio

This article considers the extension of two-grid $hp$-version discontinuous Galerkin finite element methods for the numerical approximation of second-order quasilinear elliptic boundary value problems of monotone type to the case when…

Numerical Analysis · Mathematics 2021-12-10 Scott Congreve , Paul Houston

We present algebraic multilevel iteration (AMLI) methods for isogeometric discretization of scalar second order elliptic problems. The construction of coarse grid operators and hierarchical complementary operators are given. Moreover, for a…

Numerical Analysis · Mathematics 2013-10-08 K. P. S. Gahalaut , S. K. Tomar , J. K. Kraus

This work studies three multigrid variants for matrix-free finite-element computations on locally refined meshes: geometric local smoothing, geometric global coarsening, and polynomial global coarsening. We have integrated the algorithms…

Numerical Analysis · Mathematics 2022-04-12 Peter Munch , Timo Heister , Laura Prieto Saavedra , Martin Kronbichler

Regressions created from experimental or simulated data enable the construction of metamodels, widely used in a variety of engineering applications. Many engineering problems involve multi-parametric physics whose corresponding…

Computational Engineering, Finance, and Science · Computer Science 2021-03-10 Abel Sancarlos , Victor Champaney , Jean-Louis Duval , Elias Cueto , Francisco Chinesta

The recent introduction of learned indexes has shaken the foundations of the decades-old field of indexing data structures. Combining, or even replacing, classic design elements such as B-tree nodes with machine learning models has proven…

Data Structures and Algorithms · Computer Science 2020-05-08 Paolo Ferragina , Giorgio Vinciguerra

Algorithms for many hypergraph problems, including partitioning, utilize multilevel frameworks to achieve a good trade-off between the performance and the quality of results. In this paper we introduce two novel aggregative coarsening…

Data Structures and Algorithms · Computer Science 2022-06-16 Ruslan Shaydulin , Ilya Safro

Lattice metamaterials enable lightweight, multifunctional structures, yet homogenization-based evaluation of their effective properties remains computationally expensive. Neural surrogates offer speed but often lack the accuracy and…

Graphics · Computer Science 2026-04-30 Yu Xing , Yang Liu , Tianyang Xue , Lin Lu

This work is related to PHG (Parallel Hierarchical Grid). PHG is a toolbox for developing parallel adaptive finite element programs, which is under active development at the State Key Laboratory of Scientific and Engineering Computing. The…

Computational Engineering, Finance, and Science · Computer Science 2016-11-28 Hui Liu

This paper introduces a material-aware strength-of-connection measure for smoothed aggregation algebraic multigrid methods, aimed at improving robustness for scalar partial differential equations with heterogeneous and anisotropic material…

Computational Engineering, Finance, and Science · Computer Science 2026-02-06 Max Firmbach , Malachi Phillips , Christian Glusa , Alexander Popp , Christopher M. Siefert , Matthias Mayr

The geometric high-order regularization methods such as mean curvature and Gaussian curvature, have been intensively studied during the last decades due to their abilities in preserving geometric properties including image edges, corners,…

Image and Video Processing · Electrical Eng. & Systems 2023-03-22 Zhenwei Zhang , Ke Chen , Ke Tang , Yuping Duan

Problems in scientific computing, such as distributing large sparse matrix operations, have analogous formulations as hypergraph partitioning problems. A hypergraph is a generalization of a traditional graph wherein "hyperedges" may connect…

Data Structures and Algorithms · Computer Science 2022-06-16 Justin Sybrandt , Ruslan Shaydulin , Ilya Safro

Modelling and understanding properties of materials from first principles require knowledge of the underlying atomistic structure. This entails knowing the individual identity and position of all involved atoms. Obtaining such information…

Chemical Physics · Physics 2023-07-06 Mads-Peter Verner Christiansen , Nikolaj Rønne , Bjørk Hammer

Motivation: Despite its great success in various physical modeling, differential geometry (DG) has rarely been devised as a versatile tool for analyzing large, diverse and complex molecular and biomolecular datasets due to the limited…

Quantitative Methods · Quantitative Biology 2018-06-12 Duc Duy Nguyen , Guo-Wei Wei

It is well known that multigrid methods are optimally efficient for solution of elliptic equations (O(N)), which means that effort is proportional to the number of points at which the solution is evaluated). Thus this is an ideal method to…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Vishnu Natchu , Richard A. Matzner

Numerical simulations of quantum chromodynamics (QCD) on a lattice require the frequent solution of linear systems of equations with large, sparse and typically ill-conditioned matrices. Algebraic multigrid methods are meanwhile the…

Numerical Analysis · Mathematics 2023-03-28 Jesus Espinoza-Valverde , Andreas Frommer , Gustavo Ramirez-Hidalgo , Matthias Rottmann

Many subsurface engineering applications involve tight-coupling between fluid flow, solid deformation, fracturing, and similar processes. To better understand the complex interplay of different governing equations, and therefore design…

In this paper, we consider a classical form of optimal algebraic multigrid (AMG) interpolation that directly minimizes the two-grid convergence rate and compare it with the so-called ideal form that minimizes a certain weak approximation…

Numerical Analysis · Mathematics 2017-03-31 James Brannick , Fei Cao , Karsten Kahl , Rob Falgout , Xiaozhe Hu

Automated algorithm selection for continuous black-box optimization depends on representing problem information under limited probing and selecting solvers under heavy-tailed performance distributions. This paper proposes a geometric…

Machine Learning · Computer Science 2026-05-22 Jiabao Brad Wang , Xiang Shi , Yiliang Yuan , Mustafa Misir

We present a geometric multigrid solver based on adaptive smoothed aggregation suitable for Discontinuous Galerkin (DG) discretisations. Mesh hierarchies are formed via domain decomposition techniques, and the method is applicable to fully…

Numerical Analysis · Mathematics 2025-06-02 Yulong Pan , Michael Lindsey , Per-Olof Persson