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Several recent works have developed a new, probabilistic interpretation for numerical algorithms solving linear systems in which the solution is inferred in a Bayesian framework, either directly or by inferring the unknown action of the…

Computation · Statistics 2018-10-18 Simon Bartels , Jon Cockayne , Ilse C. F. Ipsen , Philipp Hennig

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

An interfacial approximation of the streamer stage in the evolution of sparks and lightning can be written as a Laplacian growth model regularized by a `kinetic undercooling' boundary condition. We study the linear stability of uniformly…

Pattern Formation and Solitons · Physics 2009-04-16 Saleh Tanveer , Lothar Schaefer , Fabian Brau , Ute Ebert

In optimization routines used for on-line Model Predictive Control (MPC), linear systems of equations are usually solved in each iteration. This is true both for Active Set (AS) methods as well as for Interior Point (IP) methods, and for…

Optimization and Control · Mathematics 2014-01-08 Daniel Axehill

In this paper, we present a preconditioned variant of the generalized successive overrelaxation (GSOR) iterative method for solving a broad class of complex symmetric linear systems. We study conditions under which the spectral radius of…

Numerical Analysis · Mathematics 2014-10-10 Davod Hezari , Vahid Edalatpour , Davod Khojasteh Salkuyeh

The goal of this work is to present a fast and viable approach for the numerical solution of the high-contrast state problems arising in topology optimization. The optimization process is iterative, and the gradients are obtained by an…

Numerical Analysis · Mathematics 2020-06-25 Miguel Zambrano , Sintya Serrano , Boyan S. Lazarov , Juan Galvis

In geometry processing, numerical optimization methods often involve solving sparse linear systems of equations. These linear systems have a structure that strongly resembles to adjacency graphs of the underlying mesh. We observe how…

Numerical Analysis · Computer Science 2015-10-06 Nicolas Ray , Sokolov Dmitry

Recently, Garcke et al.[Garcke, Hinze, Kahle, A stable and linear time discretization for a thermodynamically consistent model for two-phase incompressible flow, Applied Numerical Mathematics 99, pp. 151-171, 2016] developed a consistent…

Numerical Analysis · Mathematics 2017-02-16 Jessica Bosch , Christian Kahle , Martin Stoll

An adapted deflation preconditioner is employed to accelerate the solution of linear systems resulting from the discretization of fracture mechanics problems with well-conditioned extended/generalized finite elements. The deflation space…

Computational Engineering, Finance, and Science · Computer Science 2022-05-11 Konstantinos Agathos , Tim Dodwell , Eleni Chatzi , Stephane P. A. Bordas

We present a compressed representation of tries based on top tree compression [ICALP 2013] that works on a standard, comparison-based, pointer machine model of computation and supports efficient prefix search queries. Namely, we show how to…

Data Structures and Algorithms · Computer Science 2019-09-23 Philip Bille , Inge Li Gørtz , Paweł Gawrychowski , Gad M. Landau , Oren Weimann

A domain decomposition method for the solution of general variable-coefficient elliptic partial differential equations on regular domains is introduced. The method is based on tessellating the domain into overlapping thin slabs or shells,…

Numerical Analysis · Mathematics 2025-10-31 Simon Dirckx , Anna Yesypenko , Per-Gunnar Martinsson

We consider the problem of learning underlying tree structure from noisy, mixed data obtained from a linear model. To achieve this, we use the expectation maximization algorithm combined with Chow-Liu minimum spanning tree algorithm. This…

Information Theory · Computer Science 2017-10-06 Navid Tafaghodi Khajavi

We present a derivative-based algorithm for nonlinearly constrained optimization problems that is tolerant of inaccuracies in the data. The algorithm solves a semi-smooth set of nonlinear equations that are equivalent to the first-order…

Optimization and Control · Mathematics 2017-09-21 Jason E. Hicken , Pengfei Meng , Alp Dener

We present a preconditioner for saddle point problems. The proposed preconditioner is extracted from a stationary iterative method which is convergent under a mild condition. Some properties of the preconditioner as well as the eigenvalues…

Numerical Analysis · Mathematics 2016-06-23 Davod Khojasteh Salkuyeh , Mohsen Masoudi

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution times for complex problems. In this…

A novel fourth-order finite difference formula coupling the Crank-Nicolson explicit linearized method is proposed to solve Riesz space fractional nonlinear reaction-diffusion equations in two dimensions. Theoretically, under the Lipschitz…

Numerical Analysis · Mathematics 2024-05-07 Wei Qu , Yuan-Yuan Huang , Sean Hon , Siu-Long Lei

This paper presents a parallel preconditioning method for distributed sparse linear systems, based on an approximate inverse of the original matrix, that adopts a general framework of distributed sparse matrices and exploits the domain…

Numerical Analysis · Computer Science 2015-06-02 Ruipeng Li , Yousef Saad

We introduce a new metric of match, called Cartesian tree matching, which means that two strings match if they have the same Cartesian trees. Based on Cartesian tree matching, we define single pattern matching for a text of length n and a…

Data Structures and Algorithms · Computer Science 2019-05-23 Sung Gwan Park , Amihood Amir , Gad M. Landau , Kunsoo Park

In this paper we consider linear systems with dense-matrices which arise from numerical solution of boundary integral equations. Such matrices can be well-approximated with $\mathcal{H}^2$-matrices. We propose several new preconditioners…

Numerical Analysis · Mathematics 2014-12-04 Daria Sushnikova , Ivan V. Oseledets

We analyze the Poisson structure of the time-dependent mean-field equations for bosons and construct the Lie-Poisson bracket associated to these equations. The latter follow from the time-dependent variational principle of Balian and…

High Energy Physics - Theory · Physics 2009-10-30 Mohamed Benarous
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