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A new reorthogonalized block classical Gram--Schmidt algorithm is proposed that factorizes a full column rank matrix $A$ into $A=QR$ where $Q$ is left orthogonal (has orthonormal columns) and $R$ is upper triangular and nonsingular. With…

Numerical Analysis · Mathematics 2011-08-23 Jesse L. Barlow , Alicja Smoktunowicz

An arbitrary $m\times n$ Boolean matrix $M$ can be decomposed {\em exactly} as $M =U\circ V$, where $U$ (resp. $V$) is an $m\times k$ (resp. $k\times n$) Boolean matrix and $\circ$ denotes the Boolean matrix multiplication operator. We…

Discrete Mathematics · Computer Science 2015-12-29 Yuan Sun , Shiwei Ye , Yi Sun , Tsunehiko Kameda

This paper investigates numerical methods for solving coupled system of nonlinear elliptic problems. We utilize block monotone iterative methods based on Jacobi and Gauss--Seidel methods to solve difference schemes which approximate the…

Numerical Analysis · Mathematics 2018-05-09 Mohamed Al-Sultani

We show that there are two or more procedures to generalize the known four-dimensional transformation, aiming to generate cylindrically rotating charged exact solutions, to higher dimensional spacetimes . In the one procedure, presented in…

General Relativity and Quantum Cosmology · Physics 2020-10-30 Mustapha Azreg-Aïnou

In these lecture notes, we present a pedagogical review of a number of related {\it numerically exact} approaches to quantum many-body problems. In particular, we focus on methods based on the exact diagonalization of the Hamiltonian matrix…

Strongly Correlated Electrons · Physics 2007-05-23 Reinhard M. Noack , Salvatore R. Manmana

The joint bidiagonalization(JBD) process is a useful algorithm for the computation of the generalized singular value decomposition(GSVD) of a matrix pair. However, it always suffers from rounding errors, which causes the Lanczos vectors to…

Numerical Analysis · Mathematics 2021-04-13 Zhongxiao Jia , Haibo Li

The main goal of this paper is to generalize Jacobi and Gauss-Seidel methods for solving non-square linear system. Towards this goal, we present iterative procedures to obtain an approximate solution for non-square linear system. We derive…

Numerical Analysis · Mathematics 2017-06-26 Manideepa Saha

For general complex or real 1-parameter matrix flows $A(t)_{n,n}$ and for time-invariant static matrices $A \in \CC_{n,n}$ alike, this paper considers ways to decompose matrix flows and single matrices globally via one constant matrix…

Numerical Analysis · Mathematics 2020-11-20 Frank Uhlig

This paper shows how to solve linear programs of the form $\min_{Ax=b,x\geq0} c^\top x$ with $n$ variables in time $$O^*((n^{\omega}+n^{2.5-\alpha/2}+n^{2+1/6}) \log(n/\delta))$$ where $\omega$ is the exponent of matrix multiplication,…

Data Structures and Algorithms · Computer Science 2020-10-21 Michael B. Cohen , Yin Tat Lee , Zhao Song

Let $M=(m_{ij})$ be a symmetric matrix of order $n$ whose elements lie in an arbitrary field $\mathbb{F}$, and let $G$ be the graph with vertex set $\{1,\ldots,n\}$ such that distinct vertices $i$ and $j$ are adjacent if and only if $m_{ij}…

Data Structures and Algorithms · Computer Science 2021-10-28 Martin Fürer , Carlos Hoppen , Vilmar Trevisan

In this work, we present a multiscale approach for the reliable coarse-scale approximation of spatial network models represented by a linear system of equations with respect to the nodes of a graph. The method is based on the ideas of the…

Numerical Analysis · Mathematics 2023-12-18 Moritz Hauck , Roland Maier , Axel Målqvist

Image restoration is typically addressed through non-convex inverse problems, which are often solved using first-order block-wise splitting methods. In this paper, we consider a general type of non-convex optimisation model that captures…

In this work we introduce and analyze a new multiscale method for strongly nonlinear monotone equations in the spirit of the Localized Orthogonal Decomposition. A problem-adapted multiscale space is constructed by solving linear local…

Numerical Analysis · Mathematics 2020-12-16 Barbara Verfürth

The joint bidiagonalization (JBD) process of a regular matrix pair $\{A,L\}$ is mathematically equivalent to two simultaneous Lanczos bidiagonalization processes of the upper and lower parts of the Q-factor of QR factorization of the…

Numerical Analysis · Mathematics 2025-03-07 Kaixiao Fang , Zhongxiao Jia

The problem of diagonalizing a class of complicated matrices, to be called ultrametric matrices, is investigated. These matrices appear at various stages in the description of disordered systems with many equilibrium phases by the technique…

Condensed Matter · Physics 2009-10-22 T. Temesvari , C De Dominicis , I. Kondor

We study the convergence of the Augmented Decomposition Algorithm (ADA) proposed in [32] for solving multi-block separable convex minimization problems subject to linear constraints. We show that the global convergence rate of the exact ADA…

Optimization and Control · Mathematics 2018-08-28 Hongsheng Liu , Shu Lu

The Semialgebraic Orbit Problem is a fundamental reachability question that arises in the analysis of discrete-time linear dynamical systems such as automata, Markov chains, recurrence sequences, and linear while loops. An instance of the…

Computational Complexity · Computer Science 2019-02-01 Shaull Almagor , Joël Oukanine , James Worrell

We present an algorithm to solve the Simultaneous Unitary Similarity(S.U.S) problem which is to check if there exists a Similarity transformation determined by a Unitary $U$ s.t $UA_lU^*=B_l$, $l \in \{1,...,p\}$, where $A_l$ and $B_l$ are…

Rings and Algebras · Mathematics 2025-12-02 Harikrishna VJ , Vittal Rao , Ramakrishnan K. R

The spectral decomposition of a real skew-symmetric matrix $A$ can be mathematically transformed into a specific structured singular value decomposition (SVD) of $A$. Based on such equivalence, a skew-symmetric Lanczos bidiagonalization…

Numerical Analysis · Mathematics 2024-08-20 Jinzhi Huang , Zhongxiao Jia

Given (orthonormal) approximations $\tilde{U}$ and $\tilde{V}$ to the left and right subspaces spanned by the leading singular vectors of a matrix $A$, we discuss methods to approximate the leading singular values of $A$ and study their…

Numerical Analysis · Mathematics 2026-01-21 Lorenzo Lazzarino , Hussam Al Daas , Yuji Nakatsukasa
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