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Using the decomposition of semimagic squares into the associated and balanced symmetry types as a motivation, we introduce an equivalent representation in terms of block-structured matrices. This block representation provides a way of…

Combinatorics · Mathematics 2016-05-30 S. L. Hill , M. C. Lettington , K. M. Schmidt

We present a spectral theory of hypergraphs that closely parallels Spectral Graph Theory. A number of recent developments building upon classical work has led to a rich understanding of "hyperdeterminants" of hypermatrices, a.k.a.…

Combinatorics · Mathematics 2011-10-27 Joshua Cooper , Aaron Dutle

Given a simple graph $G$, its $A_\alpha$ matrix is a convex combination with parameter $\alpha\in [0,1]$ of its adjacency matrix and its degree diagonal matrices. Here we compare two lower bounds presented in [J. D. G. Silva Jr., C. S.…

Combinatorics · Mathematics 2026-01-27 Giovanni Barbarino

A unified theory of orthogonal polynomials of a discrete variable is presented through the eigenvalue problem of hermitian matrices of finite or infinite dimensions. It can be considered as a matrix version of exactly solvable Schr\"odinger…

Classical Analysis and ODEs · Mathematics 2008-11-26 Satoru Odake , Ryu Sasaki

Given a set of $n$ distinct real numbers, our goal is to form a symmetric, unreduced, tridiagonal, matrix with those numbers as eigenvalues. We give an algorithm which is a stable implementation of a naive algorithm forming the…

Numerical Analysis · Mathematics 2023-11-07 Luca Dieci , Alessandro Pugliese

The problem of approximating the discrete spectra of families of self-adjoint operators that are merely strongly continuous is addressed. It is well-known that the spectrum need not vary continuously (as a set) under strong perturbations.…

Spectral Theory · Mathematics 2016-03-08 Jonathan Ben-Artzi , Thomas Holding

A simple approximate relationship between the ground-state eigenvector and the sum of matrix elements in each row has been established for real symmetric matrices with non-positive off-diagonal elements. Specifically, the $i$-th components…

Mesoscale and Nanoscale Physics · Physics 2020-11-06 Wei Pan , Jing Wang , Deyan Sun

It is well known that a family of $n\times n$ commuting matrices can be simultaneously triangularized by a unitary similarity transformation. The diagonal entries of the triangular matrices define the $n$ joint eigenvalues of the family. In…

Numerical Analysis · Mathematics 2024-11-05 Haoze He , Daniel Kressner , Bor Plestenjak

In this paper, spectral properties of matrices with (complex) zeon entries are investigated. It is shown that when $A$ is an $m\times m$ self-adjoint matrix whose characteristic polynomial $\chi_A(u)$ has $m$ ``spectrally simple'' zeros…

Rings and Algebras · Mathematics 2025-10-08 G. Stacey Staples

In this paper, we consider the problem of approximating a given matrix with a matrix whose eigenvalues lie in some specific region \Omega, within the complex plane. More precisely, we consider three types of regions and their intersections:…

Optimization and Control · Mathematics 2024-12-20 Neelam Choudhary , Nicolas Gillis , Punit Sharma

Given a square complex matrix $A$, we tackle the problem of finding the nearest matrix with multiple eigenvalues or, equivalently when $A$ had distinct eigenvalues, the nearest defective matrix. To this goal, we extend the general framework…

Numerical Analysis · Mathematics 2026-05-14 Vanni Noferini , Lauri Nyman , Federico Poloni

We obtain sequences of inclusion sets for the spectrum, essential spectrum, and pseudospectrum of banded, in general non-normal, matrices of finite or infinite size. Each inclusion set is the union of the pseudospectra of certain…

Spectral Theory · Mathematics 2023-06-21 Simon N. Chandler-Wilde , Ratchanikorn Chonchaiya , Marko Lindner

Such problems as computation of spectra of spin chains and vibrational spectra of molecules can be written as high-dimensional eigenvalue problems, i.e., when the eigenvector can be naturally represented as a multidimensional tensor. Tensor…

Numerical Analysis · Mathematics 2019-09-04 Maxim Rakhuba , Alexander Novikov , Ivan Oseledets

The tensor-tensor product (t-product) [M. E. Kilmer and C. D. Martin, 2011] is a natural generalization of matrix multiplication. Based on t-product, many operations on matrix can be extended to tensor cases, including tensor SVD, tensor…

Machine Learning · Statistics 2018-06-21 Canyi Lu

Complexity is an interdisciplinary concept which, first of all, addresses the question of how order emerges out of randomness. For many reasons matrices provide a very practical and powerful tool in approaching and quantifying the related…

Soft Condensed Matter · Physics 2008-12-18 S. Drozdz , J. Kwapien , J. Speth , M. Wojcik

Symplectic eigenvalues are conventionally defined for symmetric positive-definite matrices via Williamson's diagonal form. Many properties of standard eigenvalues, including the trace minimization theorem, are extended to the case of…

Optimization and Control · Mathematics 2022-10-11 Nguyen Thanh Son , Tatjana Stykel

Pseudospectra and structured pseudospectra are important tools for the analysis of matrices. Their computation, however, can be very demanding for all but small matrices. A new approach to compute approximations of pseudospectra and…

Numerical Analysis · Mathematics 2016-11-16 Silvia Noschese , Lothar Reichel

We study the spectral properties of certain non-self-adjoint matrices associated with large directed graphs. Asymptotically the eigenvalues converge to certain curves, apart from a finite number that have limits not on these curves.

Spectral Theory · Mathematics 2008-02-12 E. B. Davies , Paul A. Incani

The algebraic Bethe Ansatz is a prosperous and well-established method for solving one-dimensional quantum models exactly. The solution of the complex eigenvalue problem is thereby reduced to the solution of a set of algebraic equations.…

Strongly Correlated Electrons · Physics 2012-07-23 Valentin Murg , Vladimir E. Korepin , Frank Verstraete

In this paper, we describe a new algorithm that approximates the extreme eigenvalue/eigenvector pairs of a symmetric matrix. The proposed algorithm can be viewed as an extension of the Jacobi eigenvalue method for symmetric matrices…

Numerical Analysis · Mathematics 2025-09-16 Cristian Rusu