In this work, rotating beams which are isospectral to non-rotating beams are studied. A rotating beam is isospectral to a non-rotating beam if both the beams have the same spectral properties i.e; both the beams have the same set of natural frequencies under a given boundary condition. The Barcilon-Gottlieb transformation is extended, so that it converts the fourth order governing equation of a rotating beam (uniform or non-uniform), to a canonical fourth order eigenvalue equation. If the coefficients in this canonical equation match with the coefficients of the non-rotating beam (non-uniform or uniform) equation, then the rotating and non-rotating beams are isospectral to each other. The conditions on matching the coefficients lead to a pair of coupled differential equations. We solve these coupled differential equations for a particular case, and thereby obtain a class of isospectral rotating and non-rotating beams. However, to obtain isospectral beams, the transformation must leave the boundary conditions invariant. We show that the clamped end boundary condition is always invariant, and for the free end boundary condition to be invariant, we impose certain conditions on the beam characteristics. The mass and stiffness functions for the isospectral rotating and non-rotating beams are obtained. We use these mass and stiffness functions in a finite element analysis to verify numerically the isospectral property of the rotating and non-rotating beams. Finally, the example of beams having a rectangular cross section is presented to show the application of our analysis. Since experimental determination of rotating beam frequencies is a difficult task, experiments can be easily conducted on these rectangular non-rotating beams, to calculate the frequencies of the isospectral rotating beams.

Problems in the control and identification of structural dynamic systems can lead to multimodal optimization problems, which are difficult to solve using classical gradient based methods. In this work, optimization problems pertaining to the vibration control of smart structures and the exploration of isospectral systems are addressed. Isospectral vibrating systems have identical natural frequencies, and existence of the isospectral systems proves non-uniqueness in system identification. For the smart structure problem, the optimal location(s) of collocated actuator(s)/sensor(s) and the optimal feedback gain matrix are obtained by maximizing the energy dissipated by the feedback control system. For the isospectral system problem, both discrete and continuous systems are considered. An error function is designed to calculate the error between the spectra of two distinct structural dynamic systems. For the discrete system, the Jacobi matrix, derived from the given system, is modified and the problem is posed as an optimization problem where the objective is to minimize the non-negative error function. Isospectral spring-mass systems are obtained. For the continuous system, finite element modeling is used and an error function is designed to calculate the error between the spectra of the uniform beam and the non-uniform beam. Non-uniform cantilever beams which are isospectral to a given uniform cantilever beam are obtained by minimizing the non-negative error function. Numerical studies reveal several isospectral systems, and optimal gain matrices and sensor/actuator locations for the smart structure. New evolutionary algorithms, which do not need genetic operators such as crossover and mutation, are used for the optimization. These algorithms are: Artificial bee colony (ABC) algorithm, Glowworm swarm optimization (GSO) algorithm, Firefly algorithm (FA) and Electromagnetism inspired optimization (EIO) algorithm.

Bruning considered sets of isospectral Schrodinger operators with smooth real potentials on a compact manifold of dimension three. He showed the set of potentials associated to an isospectral set is compact in the topology of smooth functions by relating the spectrum to the trace of the heat semi-group. Similarly, we can consider the resonances of Schrodinger operators with real valued potentials on Euclidean space of whose support lies inside a ball of fixed radius that generate the same resonances as some fixed Schrodinger operator, an ``isoresonant" set of potentials. This isoresonant set of potentials is also compact in the topology of smooth functions for dimensions one and three. The basis of the result stems from the relation of a regularized wave trace to the resonances via the Poisson formula (also known as the Melrose trace formula). The second link is the small-t asymptotic expansion of the regularized wave trace whose coefficients are integrals of the potential function and its derivatives. For an isoresonant set these coefficients are equal due to the Poisson formula. The equivalence of coefficients allows us to uniformly bound the potential functions and their derivatives with respect to the isoresonant set. Finally, taking a sequence of functions in the isoresonant set we use the uniform bounds to construct a convergent subsequence using the Arzela-Ascoli theorem.

CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior / O som produzido por um tambor à determinado atravÃs de um conjunto de frequÃncias vibracionais. Essas frequÃncias chamadas de autovalores dependem da forma do tambor. Conhecendo os autovalores serà possÃvel determinar o formato de um tambor? Em outras palavras, serà que pode-se ouvir a forma de um tambor? Essa pergunta foi colocada por Mark Kac(KAC) em 1966 e foi um problema que levou uma boa quantidade de anos para ser resolvido. Um resultado relevante provado mais cedo foi de que pode-se ouvir a Ãrea de um tambor. Em 1910 o grande fÃsico H. A. Lorentz deu cinco palestras sob o tÃtulo geral: âVelhos e novos problemas da FÃsica" - e no final da quarta palestra, ele mostrou um problema em aberto, que em nossos termos dita uma relaÃÃo entre os autovalores e a Ãrea de um tambor. Hà um relatÃrio que Hilbert previu que esse problema nÃo seria resolvido em seu tempo de vida. Mas ele estava muito enganado, em menos de dois anos, Hermann Weyl(WEYL), que estava presente na palestra de Lorentz, prova o problema, o qual ficou conhecido por Lei de Weyl. O objetivo deste trabalho à provar a Lei de Weyl e dar um contraexemplo para o problema posto por Mark Kac. / The sound produced by a drum is determined through a set of frequencies vibrational. These frequencies eigenvalues calls depend on the shape of the drum. Knowing the eigenvalues you can determine the shape of a drum? In other words, you can hear the shape of a drum? This question was posed by Mark Kac (KAC) in 1966 and was a problem that took a good amount of years to resolved. An important result was proved earlier that you can hear the area of a drum. In 1910 the great physicist H. A. Lorentz gave five lectures under the title general: "Old and new problems of physics" - and at the end of the fourth lecture, he showed an open problem, which in our terms dictates a relationship between the eigenvalues and the area of a drum. There is a report that Hilbert predicted that this problem would not settled in their lifetime. But was very mistaken, in less than two years, Hermann Weyl (WEYL), that was present at the lecture of Lotentz, proves the problem, which was known for Weylâs law. The objective of this work is to prove the Weylâ law and give a counterexample to the problem posed by Mark Kac.

In this dissertation, we introduce three techniques for network sciences. The first of these techniques is a series of new models for describing network growth. These models, called network specialization models, are built with the idea that networks grow by specializing the function of subnetworks. Using these models we create theoretical networks which exhibit well-known properties of real networks. We also demonstrate how the spectral properties are preserved as the models grow. The second technique we describe is a method for decomposing networks that contain automorphisms in a way that preserves the spectrum of the original graph. This method for graph (or equivalently matrix) decomposition is called an equitable decomposition. Previously this method could only be used for particular classes of automorphisms, but in this dissertation we have extended this theory to work for every automorphism. Further we explain a number of applications which use equitable decompositions. The third technique we describe is a generalization of network symmetry, called latent symmetry. We give numerous examples of networks which contain latent symmetries and also prove some properties about them

The interplay between spectrum and structure of graphs is the recurring theme of the three more or less independent chapters of this thesis. The first chapter provides a method to relate the eigensolutions of two matrices, one being the principal submatrix of the other, via an arbitrary annihilating polynomial. This is extended to lambda-matrices and to matrices the entries of which are rational functions in one variable. The extension may be interpreted as a possible generalization of other known techniques which aim at reducing the size of a matrix while preserving the spectral information. Several aspects of an application in order to reduce the computational costs of ordinary eigenvalue problems are discussed. The second chapter considers the straightforward extension of the well known concept of equitable partitions to weighted graphs, i.e. complex matrices. It provides a method to divide the eigenproblem into smaller parts corresponding to the front divisor and its complementary factor in an easy and stable way with complexity which is only quadratic in matrix size. The exploitation of several equitable partitions ordered by refinement is discussed and a suggestion is made that preserves hermiticity if present. Some generalizations of equitable partitions are considered and a basic procedure for finding an equitable partition of complex matrices is given. The third chapter deals with isospectral and unitary equivalent graphs. It introduces a construction for unitary equivalent graphs which contains the well known GM-switching as a special case. It also considers an algebra of graph matrices generated by the adjacency matrix that corresponds to the 1-dimensional Weisfeiler-Lehman stabilizer in a way that mimics the correspondence of the coherent closure and the 2-dimensional Weisfeiler-Lehman stabilizer. The algebra contains the degree matrix, the (combinatorial, signless and normalized) Laplacian and the Seidel matrix. An easy construction produces graph pairs that are simultaneously unitary equivalent w.r.t. that algebra.

We give an Ansatz to construct pairs of locally homogeneous nearly Kaehler manifolds that are isospectral for the Dirac and the Hodge Laplace operator in dimensions higher than six and investigate the existence of generic isospectral pairs in dimension six.

Deux opérateurs sont étudiés dans cette thèse: l'opérateur de Schrödinger radial, issu de la mécanique quantique non relativiste; puis le système AKNS singulier, adaptation de l'opérateur de Dirac radial provenant de la mécanique quantique relativiste. La première partie consiste en la résolution du problème direct associé à chacun des deux opérateurs: détermination des valeurs et vecteurs propres, ainsi que leur dépendance vis à vis des potentiels. La présence de fonctions de Bessel due à la singularité explicite induit des difficultés lors de la détermination d'asymptotiques. La seconde partie porte sur la résolution de ces problèmes spectraux inverses. À l'aide d'opérateurs de transformations nous évitons les difficultés induites par la singularité. Ils nous permettent de développer une théorie spectrale inverse pour les opérateurs singuliers considérés. Précisément, nous construisons une application spectrale bien adapté à l'étude de la stabilité du problème inverse ainsi qu'à l'étude des ensembles isospectraux. Un résultat d'injectivité est aussi obtenu pour les opérateurs AKNS et de Dirac singuliers avec potentiels réguliers.

An isospectral algorithm is one which manipulates a matrix without changing its spectrum. In this thesis we study three interrelated examples of isospectral algorithms, all pertaining to Toeplitz matrices in some fashion, and one directly involving orthogonal polynomials. The first set of algorithms we study come from discretising a continuous isospectral flow designed to converge to a symmetric Toeplitz matrix with prescribed eigenvalues. We analyse constrained, isospectral gradient flow approaches and an isospectral flow studied by Chu in 1993. The second set of algorithms compute the spectral measure of a Jacobi operator, which is the weight function for the associated orthogonal polynomials and can include a singular part. The connection coefficients matrix, which converts between different bases of orthogonal polynomials, is shown to be a useful new tool in the spectral theory of Jacobi operators. When the Jacobi operator is a finite rank perturbation of Toeplitz, here called pert-Toeplitz, the connection coefficients matrix produces an explicit, computable formula for the spectral measure. Generalisation to trace class perturbations is also considered. The third algorithm is the infinite dimensional QL algorithm. In contrast to the finite dimensional case in which the QL and QR algorithms are equivalent, we find that the QL factorisations do not always exist, but that it is possible, at least in the case of pert-Toeplitz Jacobi operators, to implement shifts to generate rapid convergence of the top left entry to an eigenvalue. A fascinating novelty here is that the infinite dimensional matrices are computed in their entirety and stored in tailor made data structures. Lastly, the connection coefficients matrix and the orthogonal transformations computed in the QL iterations can be combined to transform these pert-Toeplitz Jacobi operators isospectrally to a canonical form. This allows us to implement a functional calculus for pert-Toeplitz Jacobi operators.

This thesis advances the theory of network specialization by characterizing the effect of network specialization on the eigenvectors of a network. We prove and provide explicit formulas for the eigenvectors of specialized graphs based on the eigenvectors of their parent graphs. The second portion of this thesis applies network specialization to learning problems. Our work focuses on training reservoir computers to mimic the Lorentz equations. We experiment with random graph, preferential attachment and small world topologies and demonstrate that the random removal of directed edges increases predictive capability of a reservoir topology. We then create a new network model by growing networks via targeted application of the specialization model. This is accomplished iteratively by selecting top preforming nodes within the reservoir computer and specializing them. Our generated topology out-preforms all other topologies on average.