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We present a fast direct solver for structured linear systems based on multilevel matrix compression. Using the recently developed interpolative decomposition of a low-rank matrix in a recursive manner, we embed an approximation of the…

Numerical Analysis · Mathematics 2014-04-10 Kenneth L. Ho , Leslie Greengard

The paper describes a sparse direct solver for the linear systems that arise from the discretization of an elliptic PDE on a two dimensional domain. The scheme decomposes the domain into thin subdomains, or ``slabs'' and uses a two-level…

Numerical Analysis · Mathematics 2025-09-01 Anna Yesypenko , Per-Gunnar Martinsson

An algorithm for the direct inversion of the linear systems arising from Nystrom discretization of integral equations on one-dimensional domains is described. The method typically has O(N) complexity when applied to boundary integral…

Numerical Analysis · Mathematics 2011-05-27 Adrianna Gillman , Patrick Young , Per-Gunnar Martinsson

A numerical method for solving elliptic PDEs with variable coefficients on two-dimensional domains is presented. The method is based on high-order composite spectral approximations and is designed for problems with smooth solutions. The…

Numerical Analysis · Mathematics 2013-07-11 A. Gillman , P. G. Martinsson

In this article, we consider fast direct solvers for nonlocal operators. The pivotal idea is to combine a wavelet representation of the system matrix, yielding a quasi-sparse matrix, with the nested dissection ordering scheme. The latter…

Numerical Analysis · Mathematics 2021-02-03 Helmut Harbrecht , Michael Multerer

This survey describes a class of methods known as "fast direct solvers". These algorithms address the problem of solving a system of linear equations $\boldsymbol{Ax}=\boldsymbol{b}$ arising from the discretization of either an elliptic PDE…

Numerical Analysis · Mathematics 2025-11-12 Per-Gunnar Martinsson , Michael O'Neil

We present a fast sparse matrix permutation algorithm tailored to linear systems arising from triangle meshes. Our approach produces nested-dissection-style permutations while significantly reducing permutation runtime overhead. Rather than…

A discretization scheme for variable coefficient Helmholtz problems on two-dimensional domains is presented. The scheme is based on high-order spectral approximations and is designed for problems with smooth solutions. The resulting system…

Numerical Analysis · Mathematics 2012-06-20 P. G. Martinsson

In many problems in Computational Physics and Chemistry, one finds a special kind of sparse matrices, termed "banded matrices". These matrices, which are defined as having non-zero entries only within a given distance from the main…

Computational Physics · Physics 2013-06-21 Pablo García-Risueño , Pablo Echenique

An efficient direct solver for volume integral equations with O(N) complexity for a broad range of problems is presented. The solver relies on hierarchical compression of the discretized integral operator, and exploits that off-diagonal…

Numerical Analysis · Mathematics 2013-05-16 Eduardo Corona , Per-Gunnar Martinsson , Denis Zorin

The well-known discrete Fourier transform (DFT) can easily be generalized to arbitrary nodes in the spatial domain. The fast procedure for this generalization is referred to as nonequispaced fast Fourier transform (NFFT). Various…

Numerical Analysis · Mathematics 2025-06-09 Melanie Kircheis , Daniel Potts

We introduce a fast direct solver for variable-coefficient elliptic partial differential equations on surfaces based on the hierarchical Poincar\'e-Steklov method. The method takes as input an unstructured, high-order quadrilateral mesh of…

Numerical Analysis · Mathematics 2022-10-04 Daniel Fortunato

The dense matrix resulting from an integral equation (IE) based solution of Maxwell's equations can be compactly represented by an ${\cal H}^2$-matrix. Given a general dense ${\cal H}^2$-matrix, prevailing fast direct solutions involve…

Numerical Analysis · Mathematics 2018-01-22 Miaomiao Ma , Dan Jiao

The large sparse linear systems arising from the finite element or finite difference discretization of elliptic PDEs can be solved directly via, e.g., nested dissection or multifrontal methods. Such techniques reorder the nodes in the grid…

Numerical Analysis · Mathematics 2013-02-26 Adrianna Gillman , Per-Gunnar Martinsson

In this paper we show how to recover a spectral approximations to broad classes of structured matrices using only a polylogarithmic number of adaptive linear measurements to either the matrix or its inverse. Leveraging this result we obtain…

Data Structures and Algorithms · Computer Science 2018-12-18 Arun Jambulapati , Kirankumar Shiragur , Aaron Sidford

Focusing inversion of potential field data for the recovery of sparse subsurface structures from surface measurement data on a uniform grid is discussed. For the uniform grid the model sensitivity matrices exhibit block Toeplitz Toeplitz…

Geophysics · Physics 2022-08-16 Rosemary A. Renaut , Jarom D. Hogue , Saeed Vatankhah

In this article, we introduce a fast and memory efficient solver for sparse matrices arising from the finite element discretization of elliptic partial differential equations (PDEs). We use a fast direct (but approximate) multifrontal…

Numerical Analysis · Computer Science 2015-04-23 AmirHossein Aminfar , Eric Darve

We developed fast direct solver for 3D Helmholtz and Maxwell equations in layered medium. The algorithm is based on the ideas of cyclic reduction for separable matrices. For the grids with major uniform part (within the survey domain in the…

Numerical Analysis · Mathematics 2019-09-04 Vladimir Druskin , Mikhail Zaslavsky

Although some preconditioners are available for solving dense linear systems, there are still many matrices for which preconditioners are lacking, in particular in cases where the size of the matrix $N$ becomes very large. There remains…

Numerical Analysis · Mathematics 2016-02-05 Pieter Coulier , Hadi Pouransari , Eric Darve

We consider the problem of estimating log-determinants of large, sparse, positive definite matrices. A key focus of our algorithm is to reduce computational cost, and it is based on sparse approximate inverses. The algorithm can be…

Numerical Analysis · Mathematics 2024-03-22 Owen Deen , Colton River Waller , John Paul Ward
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