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We compare a number of different definitions of structure algebras and TKK constructions for Jordan (super)algebras appearing in the literature. We demonstrate that, for unital superalgebras, all the definitions of the structure algebra and…

Rings and Algebras · Mathematics 2017-07-20 Sigiswald Barbier , Kevin Coulembier

Multidimensional systems are becoming increasingly important as they provide a promising tool for estimation, simulation and control, while going beyond the traditional setting of one-dimensional systems. The analysis of multidimensional…

Systems and Control · Computer Science 2018-05-08 Philippe Dreesen , Kim Batselier , Bart De Moor

We survey recent progress on efficient algorithms for approximately diagonalizing a square complex matrix in the models of rational (variable precision) and finite (floating point) arithmetic. This question has been studied across several…

Symbolic Computation · Computer Science 2023-05-19 Nikhil Srivastava

We extend the existing skew polynomial representations of matrix algebras which are direct sum of matrix spaces over division rings. In this representation, the sum-rank distance between two tuples of matrices is captured by a weight…

Information Theory · Computer Science 2025-12-10 Alessandro Neri , Paolo Santonastaso

Decomposition of large matrix inequalities for matrices with chordal sparsity graph has been recently used by Kojima et al.\ \cite{kim2011exploiting} to reduce problem size of large scale semidefinite optimization (SDO) problems and thus…

Optimization and Control · Mathematics 2021-05-19 Michal Kocvara

We use algebraic geometry to study matrix rigidity, and more generally, the complexity of computing a matrix-vector product, continuing a study initiated by Kumar, et. al. We (i) exhibit many non-obvious equations testing for (border)…

Computational Complexity · Computer Science 2015-03-11 Fulvio Gesmundo , Jonathan Hauenstein , Christian Ikenmeyer , JM Landsberg

Matrix multiplication (hereafter we use the acronym MM) is among the most fundamental operations of modern computations. The efficiency of its performance depends on various factors, in particular vectorization, data movement and arithmetic…

Data Structures and Algorithms · Computer Science 2015-02-09 Victor Y. Pan

Matrix operations such as matrix inversion, eigenvalue decomposition, singular value decomposition are ubiquitous in real-world applications. Unfortunately, many of these matrix operations so time and memory expensive that they are…

Mathematical Software · Computer Science 2015-11-04 Shusen Wang

Motivated by Kontsevich's graph complexes, this paper gives a systematic study of matroid complexes. We construct deletion and contraction bicomplexes on the vector space spanned by matroid classes equipped with ground-set orientations,…

Combinatorics · Mathematics 2026-05-26 Juliette Bruce , Jacob Bucciarelli , Bailee Zacovic

A procedure to obtain differentiation matrices is extended straightforwardly to yield new differentiation matrices useful to obtain derivatives of complex rational functions. Such matrices can be used to obtain numerical solutions of some…

Numerical Analysis · Mathematics 2007-05-23 Rafael G. Campos , Claudio Meneses

Low-rank decomposition, particularly Singular Value Decomposition (SVD), is a pivotal technique for mitigating the storage and computational demands of Large Language Models (LLMs). However, prevalent SVD-based approaches overlook the…

Machine Learning · Computer Science 2026-01-15 Lin Xv , Xian Gao , Ting Li , Yuzhuo Fu

We decompose a matrix Y into a sum of bilinear terms in a stepwise manner, by considering Y as a mapping from a finite dimensional Banach space into another finite dimensional Banach space. We provide transition formulas, and represent them…

Applications · Statistics 2015-08-28 Vartan Choulakian

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

An enhanced Kogbetliantz method for the singular value decomposition (SVD) of general matrices of order two is proposed. The method consists of three phases: an almost exact prescaling, that can be beneficial to the LAPACK's xLASV2 routine…

Numerical Analysis · Mathematics 2026-02-10 Vedran Novaković

This article makes the key observation that when using cylindrical algebraic decomposition (CAD) to solve a problem with respect to a set of polynomials, it is not always the signs of those polynomials that are of paramount importance but…

Symbolic Computation · Computer Science 2013-07-10 Russell Bradford , James H. Davenport , Matthew England , Scott McCallum , David Wilson

Recollements of derived module categories are investigated, using a new technique, ladders of recollements, which are mutation sequences. The position in the ladder is shown to control whether a recollement restricts from unbounded to…

Representation Theory · Mathematics 2016-09-29 Lidia Angeleri H\" ugel , Steffen Koenig , Qunhua Liu , Dong Yang

The Singular Value Decomposition is a matrix decomposition technique widely used in the analysis of multivariate data, such as complex space-time images obtained in both physical and biological systems. In this paper, we examine the…

Statistical Mechanics · Physics 2009-09-25 A. M. Sengupta , P. P. Mitra

This is the second installment of an exposition of an ACL2 formalization of elementary linear algebra. It extends the results of Part I, which covers the algebra of matrices over a commutative ring, but focuses on aspects of the theory that…

Discrete Mathematics · Computer Science 2025-07-28 David Russinoff

We define a special matrix multiplication among a special subset of $2N\x 2N$ matrices, and study the resulting (non-associative) algebras and their subalgebras. We derive the conditions under which these algebras become alternative…

High Energy Physics - Theory · Physics 2009-10-31 J Daboul , R Delbourgo

In our article we consider some algebraical methods which may be useful in some inverse spectral problems. The reconstraction of the matrix from its minors is considered.

Commutative Algebra · Mathematics 2007-05-23 A. V. Mouftakhov
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