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Using the block vec matrix, I give a necessary and sufficient condition for factorization of a matrix into the Kronecker product of two other matrices. As a consequence, I obtain an elementary algorithmic procedure to decide whether a…

General Mathematics · Mathematics 2013-11-12 Ignacio Ojeda

We solve the problem of characterizing the Kronecker structure of a matrix pencil obtained by a rank-one perturbation of another matrix pencil. The results hold over arbitrary fields.

Combinatorics · Mathematics 2019-12-19 Itziar Baragaña , Alicia Roca

Translated into the language of representations of quivers, a challenge in matrix pencil theory is to find sufficient and necessary conditions for a Kronecker representation to be a subfactor of another Kronecker representation in terms of…

Representation Theory · Mathematics 2007-05-23 Yang Han

Many applications give rise to structured matrix polynomials. The problem of constructing structure-preserving strong linearizations of structured matrix polynomials is revisited in this work and in the forthcoming ones…

Numerical Analysis · Mathematics 2016-06-07 Heike Faßbender , Javier Perez , Nikta Shayanfar

We introduce a new family of strong linearizations of matrix polynomials---which we call "block Kronecker pencils"---and perform a backward stability analysis of complete polynomial eigenproblems. These problems are solved by applying any…

Numerical Analysis · Mathematics 2017-07-18 Froilán M. Dopico , Piers W. Lawrence , Javier Pérez , Paul Van Dooren

The change of the Kronecker structure of a matrix pencil perturbed by another pencil of rank one has been characterized in terms of the homogeneous invariant factors and the chains of column and row minimal indices of the initial and the…

Rings and Algebras · Mathematics 2024-02-12 Itziar Baragaña , Alicia Roca

We prove that the border rank of the Kronecker square of the little Coppersmith-Winograd tensor $T_{cw,q}$ is the square of its border rank for $q > 2$ and that the border rank of its Kronecker cube is the cube of its border rank for $q >…

Computational Complexity · Computer Science 2021-12-28 Austin Conner , Fulvio Gesmundo , Joseph M. Landsberg , Emanuele Ventura

The square root rank of a nonnegative matrix $A$ is the minimum rank of a matrix $B$ such that $A=B \circ B$, where $\circ$ denotes entrywise product. We show that the square root rank of the slack matrix of the correlation polytope is…

Computational Complexity · Computer Science 2014-11-26 Troy Lee , Zhaohui Wei

In this paper, we study the asymptotic nonnegative rank of matrices, which characterizes the asymptotic growth of the nonnegative rank of fixed nonnegative matrices under the Kronecker product. This quantity is important since it governs…

Information Theory · Computer Science 2024-01-30 Yeow Meng Chee , Quoc Tung Le , Hoang Ta

We determine the border ranks of tensors that could potentially advance the known upper bound for the exponent $\omega$ of matrix multiplication. The Kronecker square of the small $q=2$ Coppersmith-Winograd tensor equals the $3\times 3$…

Algebraic Geometry · Mathematics 2020-09-25 Austin Conner , Hang Huang , J. M. Landsberg

We investigate the iterated Kronecker product of a square matrix with itself and prove an invariance property for symmetric subspaces. This motivates the definition of an iterated symmetric Kronecker product and the derivation of an…

Numerical Analysis · Mathematics 2017-09-27 George A. Hagedorn , Caroline Lasser

This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. In this paper we: establish general facts about rank decompositions of tensors, describe potential ways to search for new matrix…

Computational Complexity · Computer Science 2016-10-27 Luca Chiantini , Christian Ikenmeyer , J. M. Landsberg , Giorgio Ottaviani

We investigate the construction of circulant matrices derived from primitive roots over finite fields. Our approach reduces exponential sums to Jacobi sums, thereby establishing explicit connections between character theory and matrix…

General Mathematics · Mathematics 2026-01-19 Kenichi Takemura

The starting point for this work is an identity that relates the number of minimal matrices with prescribed 1-marginals and coefficient sequence to a linear combination of Kronecker coefficients. In this paper we provide a bijection that…

Combinatorics · Mathematics 2014-06-12 Diana Avella-Alaminos , Ernesto Vallejo

We consider the problem of approximately reconstructing a partially-observed, approximately low-rank matrix. This problem has received much attention lately, mostly using the trace-norm as a surrogate to the rank. Here we study low-rank…

Machine Learning · Computer Science 2011-05-27 Rina Foygel , Nathan Srebro

A matrix completion problem is to recover the missing entries in a partially observed matrix. Most of the existing matrix completion methods assume a low rank structure of the underlying complete matrix. In this paper, we introduce an…

Machine Learning · Statistics 2020-11-16 Chencheng Cai , Rong Chen , Han Xiao

Under the action of the general linear group with tensor structure, the ranks of matrices $A$ and $B$ forming an $m \times n$ pencil $A + \lambda B$ can change, but in a restricted manner. Specifically, with every pencil one can associate a…

Numerical Analysis · Mathematics 2018-06-20 José Henrique de Morais Goulart , Pierre Comon

Let $A$ be a square matrix with a given structure (e.g. real matrix, sparsity pattern, Toeplitz structure, etc.) and assume that it is unstable, i.e. at least one of its eigenvalues lies in the complex right half-plane. The problem of…

Numerical Analysis · Mathematics 2024-02-23 Nicola Guglielmi , Stefano Sicilia

By a tensor we mean an element of a tensor product of vector spaces over a field. Up to a choice of bases in factors of tensor products, every tensor may be coordinatized, that is, represented as an array consisting of numbers. This note is…

Functional Analysis · Mathematics 2019-01-11 R. N. Gumerov , A. S. Sharafutdinov

We study the differential and metric structures of the set of real square roots of a non-singular real matrix, under the assumption that the matrix and its square roots are semi-simple, or symmetric, or orthogonal.

Differential Geometry · Mathematics 2020-10-30 Alberto Dolcetti , Donato Pertici
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