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The spectra of signed matrices have played a fundamental role in social sciences, graph theory, and control theory. In this work, we investigate the computational problems of identifying symmetric signings of matrices with natural spectral…

Discrete Mathematics · Computer Science 2017-07-25 Charles Carlson , Karthekeyan Chandrasekaran , Hsien-Chih Chang , Alexandra Kolla

A new sufficient condition for a list of real numbers to be the spectrum of a symmetric doubly stochastic matrix is presented; this is a contribution to the classical spectral inverse problem for symmetric doubly stochastic matrices that is…

Spectral Theory · Mathematics 2020-01-27 Michal Gnacik , Tomasz Kania

An $n\times n$ matrix is said to have a self-interlacing spectrum if its eigenvalues $\lambda_k$, $k=1,\ldots,n$, are distributed as follows $$ \lambda_1>-\lambda_2>\lambda_3>\cdots>(-1)^{n-1}\lambda_n>0. $$ A method for constructing sign…

Classical Analysis and ODEs · Mathematics 2025-07-01 Mikhail Tyaglov

It is shown that for a given infinite graph $G$ on countably many vertices, and a compact, infinite set of real numbers $\Lambda$ there is a real symmetric matrix $A$ whose graph is $G$ and its spectrum is $\Lambda$. Moreover, the set of…

Spectral Theory · Mathematics 2016-10-06 Keivan Hassani Monfared , Ehssan Khanmohammadi

We study the inverse eigenvalue problem for finding doubly stochastic matrices with specified eigenvalues. By making use of a combination of Dykstra's algorithm and an alternating projection process onto a non-convex set, we derive hybrid…

Numerical Analysis · Mathematics 2023-05-31 Kassem Rammal , Bassam Mourad , Hassan Abbas , Hassan Issa

In this note, we present an algorithm that yields many new methods for constructing doubly stochastic and symmetric doubly stochastic matrices for the inverse eigenvalue problem. In addition, we introduce new open problems in this area that…

Spectral Theory · Mathematics 2012-02-15 Bassam Mourad , Hassan Abbas , Ayman Mourad , Ahmad Ghaddar , Issam Kaddoura

Two graphs are co-spectral if their respective adjacency matrices have the same multi-set of eigenvalues. A graph is said to be determined by its spectrum if all graphs that are co-spectral with it are isomorphic to it. We consider these…

Logic in Computer Science · Computer Science 2016-09-15 Anuj Dawar , Simone Severini , Octavio Zapata

The inverse eigenvalue problem of a given graph $G$ is to determine all possible spectra of real symmetric matrices whose off-diagonal entries are governed by the adjacencies in $G$. Barrett et al. introduced the Strong Spectral Property…

The still-unsolved problem of determining the set of eigenvalues realized by $n$-by-$n$ doubly stochastic matrices, those matrices with row sums and column sums equal to $1$, has attracted much attention in the last century. This problem is…

Spectral Theory · Mathematics 2020-04-06 Eric Jankowski , Charles R. Johnson , Derek Lim

It is well known that a graph is bipartite if and only if the spectrum of its adjacency matrix is symmetric. In the present paper, this assertion is dissected into three separate matrix results of wider scope, which are extended also to…

Combinatorics · Mathematics 2016-05-11 V. Nikiforov

The distance matrix of a connected graph is defined as the matrix in which the entries are the pairwise distances between vertices. The distance spectrum of a graph is the set of eigenvalues of its distance matrix. A graph is said to be…

Combinatorics · Mathematics 2022-01-10 Anuj Sakarda , Jerry Tan , Armaan Tipirneni

We investigate properties of signed graphs that have few distinct eigenvalues together with a symmetric spectrum. Our main contribution is to determine all signed $(0,2)$-graphs with vertex degree at most $6$ that have precisely two…

Combinatorics · Mathematics 2021-07-27 Gary R. W. Greaves , Zoran Stanić

The inverse eigenvalue problem of a graph studies the real symmetric matrices whose off-diagonal pattern is prescribed by the adjacencies of the graph. The strong spectral property (SSP) is an important tool for this problem. This note…

Combinatorics · Mathematics 2022-04-19 Shaun M. Fallat , H. Tracy Hall , Jephian C. -H. Lin , Bryan L. Shader

Let $A$ be a $n\times n$ complex Hermitian matrix and let $\lambda(A)=(\lambda_1,\ldots,\lambda_n)\in \mathbb{R}^n$ denote the eigenvalues of $A$, counting multiplicities and arranged in non-increasing order. Motivated by problems arising…

Functional Analysis · Mathematics 2021-04-15 Pedro Massey , Demetrio Stojanoff , Sebastian Zarate

A square matrix of order $n$ with $n\geq 2$ is called a \textit{permutative matrix} or permutative when all its rows (up to the first one) are permutations of precisely its first row. In this paper, the spectra of a class of permutative…

Spectral Theory · Mathematics 2017-08-08 Cristina B. Manzaneda , Enide Andrade , María Robbiano

A $n\times n$ matrix $A$, which has a certain sign-symmetric structure ($J$--sign-symmetric), is studied in this paper. It is shown that such a matrix is similar to a nonnegative matrix. The existence of the second in modulus positive…

Spectral Theory · Mathematics 2010-02-16 O. Y. Kushel

A new class of sign-symmetric matrices is introduced in this paper. Such matrices are named J--sign-symmetric. The spectrum of a J--sign-symmetric irreducible matrix is studied under assumptions that its second compound matrix is also…

Spectral Theory · Mathematics 2009-05-26 Olga Y. Kushel

Motivated by the conjectures formulated in 2003 by Tun\c{c}el et al., we study interlacing properties of the eigenvalues of $A\otimes B + B\otimes A$ for pairs of $n$-by-$n$ matrices $A, B$. We prove that for every pair of symmetric…

Optimization and Control · Mathematics 2020-08-11 Nargiz Kalantarova , Levent Tunçel

In this work, we consider symmetric positive definite pencils depending on two parameters. That is, we are concerned with the generalized eigenvalue problem $A(x)-\lambda B(x)$, where $A$ and $B$ are symmetric matrix valued functions in…

Numerical Analysis · Mathematics 2024-02-13 Luca Dieci , Alessandra Papini , Alessandro Pugliese

Understanding the singular value spectrum of a matrix $A \in \mathbb{R}^{n \times n}$ is a fundamental task in countless applications. In matrix multiplication time, it is possible to perform a full SVD and directly compute the singular…

Data Structures and Algorithms · Computer Science 2019-01-04 Cameron Musco , Praneeth Netrapalli , Aaron Sidford , Shashanka Ubaru , David P. Woodruff
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