Chapter 1 reviews better-known factorization theorems of a square matrix. For example, a square matrix over a field can be expressed as a product of two symmetric matrices; thus square matrices over real numbers can be factorized into two diagonalizable matrices. Factorizing matrices over complex num hers into Hermitian matrices is discussed. The chapter concludes with theorems that enable one to prescribe the eigenvalues of the factors of a square matrix, with some degree of freedom. Chapter 2 proves that a square matrix over arbitrary fields (with one exception) can be expressed as a product of two diagona lizab le matrices. The next two chapters consider decomposition of singular matrices into Idempotent matrices, and of nonsingutar matrices into Involutions. Chapter 5 studies factorization of a comp 1 ex matrix into Positive-( semi )definite matrices, emphasizing the least number of such factors required / Mathematical Sciences / M.Sc. (MATHEMATICS)

Chapter 1 reviews better-known factorization theorems of a square matrix. For example, a square matrix over a field can be expressed as a product of two symmetric matrices; thus square matrices over real numbers can be factorized into two diagonalizable matrices. Factorizing matrices over complex numbers into Hermitian matrices is discussed. The chapter concludes with theorems that enable one to prescribe the eigenvalues of the factors of a square matrix, with some degree of freedom. Chapter 2 proves that a square matrix over arbitrary fields (with one exception) can be expressed as a product of two diagonalizable matrices. The next two chapters consider decomposition of singular matrices into Idempotent matrices, and of nonsingular matrices into Involutions. Chapter 5 studies factorization of a complex matrix into Positive-(semi)definite matrices, emphasizing the least number of such factors required. / Mathematical Sciences / M. Sc. (Mathematics)

Chapter 1 reviews better-known factorization theorems of a square matrix. For example, a square matrix over a field can be expressed as a product of two symmetric matrices; thus square matrices over real numbers can be factorized into two diagonalizable matrices. Factorizing matrices over complex num hers into Hermitian matrices is discussed. The chapter concludes with theorems that enable one to prescribe the eigenvalues of the factors of a square matrix, with some degree of freedom. Chapter 2 proves that a square matrix over arbitrary fields (with one exception) can be expressed as a product of two diagona lizab le matrices. The next two chapters consider decomposition of singular matrices into Idempotent matrices, and of nonsingutar matrices into Involutions. Chapter 5 studies factorization of a comp 1 ex matrix into Positive-( semi )definite matrices, emphasizing the least number of such factors required / Mathematical Sciences / M.Sc. (MATHEMATICS)

Chapter 1 reviews better-known factorization theorems of a square matrix. For example, a square matrix over a field can be expressed as a product of two symmetric matrices; thus square matrices over real numbers can be factorized into two diagonalizable matrices. Factorizing matrices over complex numbers into Hermitian matrices is discussed. The chapter concludes with theorems that enable one to prescribe the eigenvalues of the factors of a square matrix, with some degree of freedom. Chapter 2 proves that a square matrix over arbitrary fields (with one exception) can be expressed as a product of two diagonalizable matrices. The next two chapters consider decomposition of singular matrices into Idempotent matrices, and of nonsingular matrices into Involutions. Chapter 5 studies factorization of a complex matrix into Positive-(semi)definite matrices, emphasizing the least number of such factors required. / Mathematical Sciences / M. Sc. (Mathematics)

Toute perturbation dans les systèmes linéaires peut gravement dégrader la performance des méthodes itératives lorsque les directions conjuguées sont constituées. Ce problème peut être partiellement résolu par les méthodes du gradient à retards, qui ne garantissent pas la descente de la fonction quadratique, mais peuvent améliorer la convergence par rapport aux méthodes traditionnelles. Les travaux ultérieurs se sont concentrés sur les méthodes du gradient alternées avec deux ou plusieurs types de pas afin d'interrompre le zigzag. Des papiers récents ont suggéré que la révélation d'information de second ordre avec des pas à retards pourrait réduire de manière asymptotique les espaces de recherche dans des dimensions de plus en plus petites. Ceci a conduit aux méthodes du gradient avec alignement dans lesquelles l'étape essentielle et l'étape auxiliaire sont effectuées en alternance. Des expériences numériques ont démontré leur efficacité. Cette thèse considère d'abord des méthodes du gradient efficaces pour résoudre les systèmes linéaires symétriques définis positifs. Nous commençons par étudier une méthode alternée avec la propriété de terminaison finie à deux dimensions. Ensuite, nous déduisons davantage de propriétés spectrales pour les méthodes du gradient traditionnelles. Ces propriétés nous permettent d’élargir la famille de méthodes du gradient avec alignement et d’établir la convergence de nouvelles méthodes. Nous traitons également les itérations de gradient comme un processus peu coûteux intégré aux méthodes de splitting. En particulier, nous abordons le problème de l’estimation de paramètre et suggérons d’utiliser les méthodes du gradient rapide comme solveurs internes à faible précision. Dans le cas parallèle, nous nous concentrons sur les formulations avec retards pour lesquelles il est possible de réduire les coûts de communication. Nous présentons également de nouvelles propriétés et méthodes pour les itérations de gradient s-dimensionnelles. En résumé, cette thèse s'intéresse aux trois sujets interreliés dans lesquelles les itérations de gradient peuvent être utilisées en tant que solveurs efficaces, qu’outils intégrés pour les méthodes de splitting et que solveurs parallèles pour réduire la communication. Des exemples numériques sont présentés à la fin de chaque sujet pour appuyer nos résultats théoriques. / Any perturbation in linear systems may severely degrade the performance of iterative methods when conjugate directions are constructed. This issue can be partially remedied by lagged gradient methods, which does not guarantee descent in the quadratic function but can improve the convergence compared with traditional gradient methods. Later work focused on alternate gradient methods with two or more steplengths in order to break the zigzag pattern. Recent papers suggested that revealing of second-order information along with lagged steps could reduce asymptotically the search spaces in smaller and smaller dimensions. This led to gradient methods with alignment in which essential and auxiliary steps are conducted alternately. Numerical experiments have demonstrated their effectiveness. This dissertation first considers efficient gradient methods for solving symmetric positive definite linear systems. We begin by studying an alternate method with two-dimensional finite termination property. Then we derive more spectral properties for traditional steplengths. These properties allow us to expand the family of gradient methods with alignment and establish the convergence of new methods. We also treat gradient iterations as an inexpensive process embedded in splitting methods. In particular we address the parameter estimation problem and suggest to use fast gradient methods as low-precision inner solvers. For the parallel case we focus on the lagged formulations for which it is possible to reduce communication costs. We also present some new properties and methods for s-dimensional gradient iterations. To sum up, this dissertation is concerned with three inter-related topics in which gradient iterations can be employed as efficient solvers, as embedded tools for splitting methods and as parallel solvers for reducing communication. Numerical examples are presented at the end of each topic to support our theoretical findings.

We solve a random matrix ensemble called the chiral Ginibre orthogonal ensemble, or chGinOE. This non-Hermitian ensemble has applications to modelling particular low-energy limits of two-colour quantum chromo-dynamics (QCD). In particular, the matrices model the Dirac operator for quarks in the presence of a gluon gauge field of fixed topology, with an arbitrary number of flavours of virtual quarks and a non-zero quark chemical potential. We derive the joint probability density function (JPDF) of eigenvalues for this ensemble for finite matrix size N, which we then write in a factorised form. We then present two different methods for determining the correlation functions, resulting in compact expressions involving Pfaffians containing the associated kernel. We determine the microscopic large-N limits at strong and weak non-Hermiticity (required for physical applications) for both the real and complex eigenvalue densities. Various other properties of the ensemble are also investigated, including the skew-orthogonal polynomials and the fraction of eigenvalues that are real. A number of the techniques that we develop have more general applicability within random matrix theory, some of which we also explore in this thesis.

Neste trabalho se apresenta o desenvolvimento de algoritmos hermitianos de integração das equações diferenciais do filtro digital de Butterworth mediante operadores de integração numérica de ordem elevada com passo único. A teoria do filtro de Butterworth é apresentada mediante o emprego da transformada de Fourier. Exemplos de aplicação apresentados através destes algoritmos mostram que os resultados são, como esperado, mais precisos que os resultantes dos métodos usuais presentes na literatura especializada / In this work is presented the development of hermitian algorithm for integration of the Butterworth digital filter’s differential equations by means of high order numerical one step operators. The Butterworth filter’s theory is presented based on the Fourier transform. Numerical examples show that the results of the developed hermitian algorithm are more accurate than the usual methods present in the specialized literature, as expected

Simetrias compõe parte integral da análise na Teoria das Matrizes Aleatórias (RMT). As simetrias de inversão temporal e rotacional são aspectos-chave do Ensemble Gaussiano Ortogonal (GOE), enquanto esta última é quebrada no Ensemble Gaussiano Simplético (GSE) e ambas são quebradas no Conjunto Unitário Gaussiano (GUE). Desde o final da década de 1990, o crescente interesse no campo dos sistemas quânticos PT-simétricos levou os pesquisadores a considerar o efeito, em matrizes aleatórias, dessa classe de simetrias, bem como simetrias pseudo-hermitianas. A principal questão a ser respondida pela pesquisa apresentada nesta tese é se a simetria PT ou, de forma mais geral, a pseudo-Hermiticidade implica alguma distribuição de probabilidade específica para os autovalores. Ou, em outras palavras, se há um aspecto comum transmitido por tal simetria que pode ser usada para modelar alguma classe particular de sistemas físicos. A abordagem inicial considerada consistiu na introdução de um conjunto pseudo-hermitiano, isospectral ao conjunto -Hermite, que apresentaria o tipo de quebra de realidade típico dos sistemas PT-simétricos. Nesse modelo, a primeira abordagem adotada foi a introdução de perturbações que quebraram a realidade dos espectros. Os resultados obtidos permitem concluir que a transformação em seu similar pseudo-hermitiano conduz a um sistema assintoticamente instável. Esse modelo foi extendido ao considerar um pseudo-hermitiano não positivo, que leva a uma quebra similar na realidade dos espectros. Este caso apresenta um comportamento mais próximo do típico dos sistemas PT-simétricos presentes na literatura. Um modelo denso geral baseado em projetores foi proposto, e duas realizações particulares deste modelo receberam atenção mais detalhada. O comportamento espectral também foi similar àquele típico da simetria PT para as duas realizações consideradas, e seus limites assintóticos foram conectados a conjuntos clássicos de teoria de matriz aleatória. Além disso, as propriedades de seus polinômios característicos médios foram obtidas e os limites assintóticos desses polinômios também foram considerados e relacionados a polinômios clássicos. O comportamento estatístico deste conjunto foi estudado e comparado com o destes polinômios. Impor a pseudo-Hermiticidade não parece implicar qualquer distribuição particular de autovalores, sendo a característica comum a quebra da realidade dos autovalores comumente encontrados na literatura de simetria PT. O resultado mais notável dos estudos apresentados nesta tese é o fato de que uma interação pseudo-hermitiana pode ser construída de tal forma que o comportamento espectral médio possa ser controlado calibrando-se o mecanismo de interação, bem como sua intensidade. / The role of symmetries is an integral part of the analysis in Random Matrix Theory (RMT). Time reversal and rotational symmetries are key aspects of the Gaussian Orthogonal Ensemble (GOE), whereas the latter is broken in the Gaussian Sympletic Ensemble (GSE) and both are broken in the Gaussian Unitary Ensemble (GUE). Since the late 1990s, growing interest in the field of PT symmetric quantum systems has led researchers to consider the effect, in random matrices, of this class of symmetries, as well as that of pseudo-Hermitian symmetries. The primary question to be answered by the research presented in this thesis is whether PT-symmetry or, more generally, pseudo-Hermiticity implies some specific probability distribution for the eigenvalues. Or, in other words, whether there is a common aspect imparted by such a symmetry which may be used to model some particular class of physical systems. The initial approach considered consisted of introducing an pseudo-Hermitian ensemble, isospectral to the -Hermite ensemble, which would present the type of reality-breaking typical of PT-symmetrical systems. In this model, the first approach taken was to introduce perturbation which broke the reality of the spectra. The results obtained allow the conclusion that the transformation into its pseudo-Hermitian similar leads into a system which is asymptotically unstable. An extension of this model was to consider a non-positive pseudo-Hermitian , which lead to similar breaking in the reality of the spectra. This case displays behavior closer to that typical of the PT-symmetric systems present in the literature. A general dense projector model was proposed, and two particular realizations of this model were given more detailed attention. The spectral behavior was also similar to that typical of PT-symmetry for the two realizations considered, and their asymptotic limits were shown to connect to classical ensembles of random matrix theory. Furthermore, the properties of their average characteristic polynomials were obtained and the asymptotic limits of these polynomials were also considered and were related to classical polynomials. The statistical behavior of this ensemble was studied and compared to that of these polynomials. Imposing the pseudo-Hermitian does seem not imply any particular eigenvalue distribution, the common feature being the breaking of the reality of the eigenvalues commonly found in PT-symmetry literature. The most notable result of the studies presented herein is the fact that a pseudo-Hermitian interaction may be constructed such that the average spectral behavior may be controlled by calibrating the mechanism of interaction as well as its intensity.

This thesis consists of two papers devoted to the asymptotics of random matrix ensembles and measure valued stochastic processes which can be considered as generalizations of the Gaussian unitary ensemble (GUE) of Hermitian matrices H=A+A†, where the entries of A are independent identically distributed (iid) centered complex Gaussian random variables. In the first paper, a system of interacting diffusing particles on the real line is studied; special cases include the eigenvalue dynamics of matrix-valued Ornstein-Uhlenbeck processes (Dyson's Brownian motion). It is known that the empirical measure process converges weakly to a deterministic measure-valued function and that the appropriately rescaled fluctuations around this limit converge weakly to a Gaussian distribution-valued process. For a large class of analytic test functions, explicit formulae are derived for the mean and covariance functionals of this fluctuation process. The second paper concerns a family of random matrix ensembles interpolating between the GUE and the Ginibre ensemble of n x n matrices with iid centered complex Gaussian entries. The asymptotic spectral distribution in these models is uniform in an ellipse in the complex plane, which collapses to an interval of the real line as the degree of non-Hermiticity diminishes. Scaling limit theorems are proven for the eigenvalue point process at the rightmost edge of the spectrum, and it is shown that a non-trivial transition occurs between Poisson and Airy point process statistics when the ratio of the axes of the supporting ellipse is of order n -1/3. / Denna avhandling består av två vetenskapliga artiklar som handlar om gränsvärdessatser för slumpmatriser och måttvärda stokastiska processer. De modeller som studeras kan betraktas som generaliseringar av den gaussiska unitära ensembeln (GUE) av hermiteska n x n-matriser H=A+A†, där A är en matris vars element är oberoende, likafördelade, centrerade, komplexa normalfördelade stokastiska variabler. I artikel I betraktas ett system av växelverkande diffunderande partiklar på reella linjen, vissa specialfall av denna modell kan tolkas som egenvärdesdynamiken för matrisvärda Ornstein-Uhlenbeck-processer (Dysons brownska rörelse). Sedan tidigare är det känt att den empiriska måttprocessen konvergerar svagt mot en deterministisk måttvärd funktion och att fluktuationerna runt denna gräns, i lämplig skalning, konvergerer svagt mot en distributionsvärd gaussisk process. För en stor klass av analytiska testfunktioner härleds explicita formler för medelvärdes- och kovariansfunktionalerna för denna fluktuationsprocess. Artikel II behandlar en familj av slumpmatrisensembler som interpolerar mellan GUE och Ginibre-ensembeln, bestående av matriser A som ovan. För denna modell är egenvärdena komplexa och asymptotiskt likformigt fördelade i en ellips i komplexa planet. Skalningsgränsvärdessatser för egenvärdet med maximal realdel och för egenvärdespunktprocessen kring detta visas för ett allmänt val av interpolationsparametern i modellen. Då förhållandet mellan axlarna i den asymptotiska ellipsen är av storleksordning n-1/3 uppträder en övergångsfas mellan Airypunktprocess- och Poissonprocessbeteendena, typiska för GUE respektive Ginibre-ensembeln. / QC 20100705

This thesis develops ways of localizing the Ritz values of non-Hermitian matrices. The restarted Arnoldi method with exact shifts, useful for determining a few desired eigenvalues of a matrix, employs Ritz values to refine eigenvalue estimates. In the Hermitian case, using selected Ritz values produces convergence due to interlacing. No generalization of interlacing exists for non-Hermitian matrices, and as a consequence no satisfactory general convergence theory exists. To study Ritz values, I propose the inverse field of values problem for k Ritz values, which asks if a set of k complex numbers can be Ritz values of a matrix. This problem is always solvable for k = 1 for any complex number in the field of values; I provide an improved algorithm for finding a Ritz vector in this case. I show that majorization can be used to characterize, as well as localize, Ritz values. To illustrate the difficulties of characterizing Ritz values, this work provides a complete analysis of the Ritz values of two 3 × 3 matrices: a Jordan block and a normal matrix. By constructing conditions for localizing the Ritz values of a matrix with one simple, normal, sought-after eigenvalue, this work develops sufficient conditions that guarantee convergence of the restarted Arnoldi method with exact shifts. For general matrices, the conditions provide insight into the subspace dimensions that ensure that shifts do not cluster near the wanted eigenvalue. As Ritz values form the basis for many iterative methods for determining eigenvalues and solving linear systems, an understanding of Ritz value behavior for non-Hermitian matrices has the potential to inform a broad range of analysis.