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The notion of root polynomials of a polynomial matrix $P(\lambda)$ was thoroughly studied in [F. Dopico and V. Noferini, Root polynomials and their role in the theory of matrix polynomials, Linear Algebra Appl. 584:37--78, 2020]. In this…

Optimization and Control · Mathematics 2022-10-07 Vanni Noferini , Paul Van Dooren

In this paper, we develop algorithms for computing the recurrence coefficients corresponding to multiple orthogonal polynomials on the step-line. We reformulate the problem as an inverse eigenvalue problem, which can be solved using…

Numerical Analysis · Mathematics 2026-03-05 Amin Faghih , Michele Rinelli , Marc Van Barel , Raf Vandebril , Robbe Vermeiren

Given the $n\times n$ matrix polynomial $P(x)=\sum_{i=0}^kP_i x^i$, we consider the associated polynomial eigenvalue problem. This problem, viewed in terms of computing the roots of the scalar polynomial $\det P(x)$, is treated in…

Numerical Analysis · Mathematics 2012-07-27 Dario A. Bini , V. Noferini

Random matrices now play a role in many parts of computational mathematics. To advance these applications, it is desirable to have tools that are flexible, easy to use, and powerful. Over the last 25 years, researchers have developed a…

Probability · Mathematics 2026-05-01 Joel A. Tropp

Eigensolvers involving complex moments can determine all the eigenvalues in a given region in the complex plane and the corresponding eigenvectors of a regular linear matrix pencil. The complex moment acts as a filter for extracting…

Numerical Analysis · Mathematics 2021-09-22 Keiichi Morikuni

We obtain cubature formulas of volume potentials over bounded domains combining the basis functions introduced in the theory of approximate approximations with their integration over the tangential-halfspace. Then the computation is reduced…

Numerical Analysis · Mathematics 2012-10-29 F. Lanzara , V. Maz'ya , G. Schmidt

A theoretical analysis is given of the equation of motion method, due to Alben et al., to compute the eigenvalue distribution (density of states) of very large matrices. The salient feature of this method is that for matrices of the kind…

Computational Physics · Physics 2009-11-06 Anthony Hams , Hans De Raedt

Quantum algorithms are able to solve particular problems exponentially faster than conventional algorithms, when implemented on a quantum computer. However, all demonstrations to date have required already knowing the answer to construct…

Quantum Physics · Physics 2013-03-22 Xiao-Qi Zhou , Pruet Kalasuwan , Timothy C. Ralph , Jeremy L. O'Brien

In the present article we shown a formula to compute the number of all matrices over the finite field $F$ whit prescribed eigenvalues. Using this formula we obtain one inequality for the number of $(k+1)$-potent elements over finite rings.

Combinatorics · Mathematics 2020-09-01 Ivan Gargate , Michael Gargate

We provide a simple way to add, multiply, invert, and take traces and norms of algebraic integers of a number field using integral matrices. With formulas for the integral bases of the ring of integers of at least a significant proportion…

Number Theory · Mathematics 2018-09-26 Samuel A. Hambleton

We describe a dynamic programming algorithm for exact counting and exact uniform sampling of matrices with specified row and column sums. The algorithm runs in polynomial time when the column sums are bounded. Binary or non-negative integer…

Computation · Statistics 2011-04-05 Jeffrey W. Miller , Matthew T. Harrison

Low-rank matrix approximations are often used to help scale standard machine learning algorithms to large-scale problems. Recently, matrix coherence has been used to characterize the ability to extract global information from a subset of…

Machine Learning · Statistics 2010-09-07 Mehryar Mohri , Ameet Talwalkar

We describe preconditioned iterative methods for estimating the number of eigenvalues of a Hermitian matrix within a given interval. Such estimation is useful in a number of applications.In particular, it can be used to develop an efficient…

Numerical Analysis · Mathematics 2016-02-09 Eugene Vecharynski , Chao Yang

A square matrix is called stochastic (or row-stochastic) if it is non-negative and has each row sum equal to unity. Here, we constitute an eigenvalue localization theorem for a stochastic matrix, by using its principal submatrices. As an…

Combinatorics · Mathematics 2016-05-02 Anirban Banerjee , Ranjit Mehatari

Computing the determinant of a matrix with the univariate and multivariate polynomial entries arises frequently in the scientific computing and engineering fields. In this paper, an effective algorithm is presented for computing the…

Symbolic Computation · Computer Science 2015-04-14 Xiaolin Qin , Zhi Sun , Tuo Leng , Yong Feng

In this review we discuss, from a unified point of view, a variety of Monte Carlo methods used to solve eigenvalue problems in statistical mechanics and quantum mechanics. Although the applications of these methods differ widely, the…

Condensed Matter · Physics 2011-05-21 M. P. Nightingale , C. J. Umrigar

We explore the block nature of the matrix representation of multiplex networks, introducing a new formalism to deal with its spectral properties as a function of the inter-layer coupling parameter. This approach allows us to derive…

Physics and Society · Physics 2018-07-17 Guilherme Ferraz de Arruda , Emanuele Cozzo , Francisco A. Rodrigues , Yamir Moreno

We give an $O(n)$ time and space algorithm for constructing a diagonal matrix congruent to A+xI, where A is the adjacency matrix of a cograph and $x\in \mathbb{R}$. Applications include determining the number of eigenvalues of a cograph's…

Combinatorics · Mathematics 2017-04-05 David P. Jacobs , Vilmar Trevisan , Fernando C. Tura

After a short review of the classical Lie theorem, a finite dimensional Lie algebra of vector fields is considered and the most general conditions under which the integral curves of one of the fields can be obtained by quadratures in a…

Mathematical Physics · Physics 2017-01-17 José F. Cariñena , Fernando Falceto , Janusz Grabowski , Manuel F. Rañada

We lay down the foundations of the Eigenvalue Method in coding theory. The method uses modern algebraic graph theory to derive upper bounds on the size of error-correcting codes for various metrics, addressing major open questions in the…

Combinatorics · Mathematics 2025-09-24 Aida Abiad , Loes Peters , Alberto Ravagnani