An atlas for tridiagonal isospectral manifolds

Let ${\cal T}_\Lambda$ be the compact manifold of real symmetric tridiagonal matrices conjugate to a given diagonal matrix $\Lambda$ with simple spectrum. We introduce {\it bidiagonal coordinates}, charts defined on open dense domains forming an explicit atlas for ${\cal T}_\Lambda$. In contrast to the standard inverse variables, consisting of eigenvalues and norming constants, every matrix in ${\cal T}_\Lambda$ now lies in the interior of some chart domain. We provide examples of the convenience of these new coordinates for the study of asymptotics of isospectral dynamics, both for continuous and discrete time.Comment: Fixed typos; 16 pages, 3 figure

The Power of Bidiagonal Matrices

Bidiagonal matrices are widespread in numerical linear algebra, not least because of their use in the standard algorithm for computing the singular value decomposition and their appearance as LU factors of tridiagonal matrices. We show that bidiagonal matrices have a number of interesting properties that make them powerful tools in a variety of problems, especially when they are multiplied together. We show that the inverse of a product of bidiagonal matrices is insensitive to small componentwise relative perturbations in the factors if the factors or their inverses are nonnegative. We derive componentwise rounding error bounds for the solution of a linear system $Ax = b$, where $A$ or $A^{-1}$ is a product $B_1 B_2\dots B_k$ of bidiagonal matrices, showing that strong results are obtained when the $B_i$ are nonnegative or have a checkerboard sign pattern. We show that given the \fact\ of an $n\times n$ totally nonnegative matrix $A$ into the product of bidiagonal matrices, $\|A^{-1}\|_{\infty}$ can be computed in $O(n^2)$ flops and that in floating-point arithmetic the computed result has small relative error, no matter how large $\|A^{-1}\|_{\infty}$ is. We also show how factorizations involving bidiagonal matrices of some special matrices, such as the Frank matrix and the Kac--Murdock--Szeg\"o matrix, yield simple proofs of the total nonnegativity and other properties of these matrices

Numerical methods and accurate computations with structured matrices

Esta tesis doctoral es un compendio de 11 artículos científicos. El tema principal de la tesis es el Álgebra Lineal Numérica, con énfasis en dos clases de matrices estructuradas: las matrices totalmente positivas y las M-matrices. Para algunas subclases de estas matrices, es posible desarrollar algoritmos para resolver numéricamente varios de los problemas más comunes en álgebra lineal con alta precisión relativa independientemente del número de condición de la matriz. La clave para lograr cálculos precisos está en el uso de una parametrización diferente que represente la estructura especial de la matriz y en el desarrollo de algoritmos adaptados que trabajen con dicha parametrización.Las matrices totalmente positivas no singulares admiten una factorización única como producto de matrices bidiagonales no negativas llamada factorización bidiagonal. Si conocemos esta representación con alta precisión relativa, se puede utilizar para resolver ciertos sistemas de ecuaciones y para calcular la inversa, los valores propios y los valores singulares con alta precisión relativa. Nuestra contribución en este campo ha sido la obtención de la factorización bidiagonal con alta precisión relativa de matrices de colocación de polinomios de Laguerre generalizados, de matrices de colocación de polinomios de Bessel, de clases de matrices que generalizan la matriz de Pascal y de matrices de q-enteros. También hemos estudiado la extensión de varias propiedades óptimas de las matrices de colocación de B-bases normalizadas (que en particular son matrices totalmente positivas). En particular, hemos demostrado propiedades de optimalidad de las matrices de colocación del producto tensorial de B-bases normalizadas.Si conocemos las sumas de filas y las entradas extradiagonales de una M-matriz no singular diagonal dominante con alta precisión relativa, entonces podemos calcular su inversa, determinante y valores singulares también con alta precisión relativa. Hemos buscado nuevos métodos para lograr cálculos precisos con nuevas clases de M-matrices o matrices relacionadas. Hemos propuesto una parametrización para las Z-matrices de Nekrasov con entradas diagonales positivas que puede utilizarse para calcular su inversa y determinante con alta precisión relativa. También hemos estudiado la clase denominada B-matrices, que está muy relacionada con las M-matrices. Hemos obtenido un método para calcular los determinantes de esta clase con alta precisión relativa y otro para calcular los determinantes de las matrices de B-Nekrasov también con alta precisión relativa. Basándonos en la utilización de dos matrices de escalado que hemos introducido, hemos desarrollado nuevas cotas para la norma infinito de la inversa de una matriz de Nekrasov y para el error del problema de complementariedad lineal cuando su matriz asociada es de Nekrasov. También hemos obtenido nuevas cotas para la norma infinito de las inversas de Bpi-matrices, una clase que extiende a las B-matrices, y las hemos utilizado para obtener nuevas cotas del error para el problema de complementariedad lineal cuya matriz asociada es una Bpi-matriz. Algunas clases de matrices han sido generalizadas al caso de mayor dimensión para desarrollar una teoría para tensores extendiendo la conocida para el caso matricial. Por ejemplo, la definición de la clase de las B-matrices ha sido extendida a la clase de B-tensores, dando lugar a un criterio sencillo para identificar una nueva clase de tensores definidos positivos. Hemos propuesto una extensión de la clase de las Bpi-matrices a Bpi-tensores, definiendo así una nueva clase de tensores definidos positivos que puede ser identificada en base a un criterio sencillo basado solo en cálculos que involucran a las entradas del tensor. Finalmente, hemos caracterizado los casos en los que las matrices de Toeplitz tridiagonales son P-matrices y hemos estudiado cuándo pueden ser representadas en términos de una factorización bidiagonal que sirve como parametrización para lograr cálculos con alta precisión relativa.<br /

Decay properties of spectral projectors with applications to electronic structure

Motivated by applications in quantum chemistry and solid state physics, we apply general results from approximation theory and matrix analysis to the study of the decay properties of spectral projectors associated with large and sparse Hermitian matrices. Our theory leads to a rigorous proof of the exponential off-diagonal decay ("nearsightedness") for the density matrix of gapped systems at zero electronic temperature in both orthogonal and non-orthogonal representations, thus providing a firm theoretical basis for the possibility of linear scaling methods in electronic structure calculations for non-metallic systems. We further discuss the case of density matrices for metallic systems at positive electronic temperature. A few other possible applications are also discussed.Comment: 63 pages, 13 figure

Relative perturbation theory for diagonally dominant matrices

In this paper, strong relative perturbation bounds are developed for a number of linear algebra problems involving diagonally dominant matrices. The key point is to parameterize diagonally dominant matrices using their off-diagonal entries and diagonally dominant parts and to consider small relative componentwise perturbations of these parameters. This allows us to obtain new relative perturbation bounds for the inverse, the solution to linear systems, the symmetric indefinite eigenvalue problem, the singular value problem, and the nonsymmetric eigenvalue problem. These bounds are much stronger than traditional perturbation results, since they are independent of either the standard condition number or the magnitude of eigenvalues/singular values. Together with previously derived perturbation bounds for the LDU factorization and the symmetric positive definite eigenvalue problem, this paper presents a complete and detailed account of relative structured perturbation theory for diagonally dominant matrices.This research was partially supported by the Ministerio de Economía y Competitividad of Spain under grant MTM2012-32542.Publicad

Algorithms for Bohemian Matrices

This thesis develops several algorithms for working with matrices whose entries are multivariate polynomials in a set of parameters. Such parametric linear systems often appear in biology and engineering applications where the parameters represent physical properties of the system. Some computations on parametric matrices, such as the rank and Jordan canonical form, are discontinuous in the parameter values. Understanding where these discontinuities occur provides a greater understanding of the underlying system. Algorithms for computing a complete case discussion of the rank, Zigzag form, and the Jordan canonical form of parametric matrices are presented. These algorithms use the theory of regular chains to provide a unified framework allowing for algebraic or semi-algebraic constraints on the parameters. Corresponding implementations for each algorithm in the Maple computer algebra system are provided. In some applications, all entries may be parameters whose values are limited to finite sets of integers. Such matrices appear in applications such as graph theory where matrix entries are limited to the sets {0, 1}, or {-1, 0, 1}. These types of parametric matrices can be explored using different techniques and exhibit many interesting properties. A family of Bohemian matrices is a set of low to moderate dimension matrices where the entries are independently sampled from a finite set of integers of bounded height. Properties of Bohemian matrices are studied including the distributions of their eigenvalues, symmetries, and integer sequences arising from properties of the families. These sequences provide connections to other areas of mathematics and have been archived in the Characteristic Polynomial Database. A study of two families of structured matrices: upper Hessenberg and upper Hessenberg Toeplitz, and properties of their characteristic polynomials are presented