This thesis contains two main chapters. The first chapter focuses on the highdimensional asymptotic regimes of correlated Wishart matrices d−1YY^T , where Y is a n×d Gaussian random matrix with correlated and non-stationary entries. We provide quantitative bounds in the Wasserstein distance for the cases of central convergence and non-central convergence, verify such convergences hold in the weak topology of C([a; b]; M_n(R)), and show that our result can be used to prove convergence in expectation of the empirical spectral distributions of the Wishart matrices to the semicircular law. The second chapter develops a version of the Stein-Malliavin method in an infinite-dimensional and non-diffusive Poissonian setting. In particular, we provide quantitative central limit theorems for approximations by non-degenerate Hilbert-valued Gaussian random elements, as well as fourth moment bounds for approximating sequences with finite chaos expansion. We apply our results to the Brownian approximation of Poisson processes in Besov-Liouville spaces and also derive a functional limit theorem for an edge-counting statistic of a random geometric graph.

<p> In this thesis we study convexity theorems on the interpolation of linear operators between LP-spaces. An extension of the Riesz-Thorin Theorem to spaces constructed from countably many LP-spaces is given. In addition, results involving analytic families of linear operators between these spaces are obtained. </p> / Thesis / Master of Science (MSc)

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Call number: LD2668 .T4 1985 B78 / Master of Science

published_or_final_version / Mechanical Engineering / Doctoral / Doctor of Philosophy

This paper is a study of linear operators defined on normed linear spaces. A basic knowledge of set theory and vector spaces is assumed, and all spaces considered have real vector spaces. The first chapter is a general introduction that contains assumed definitions and theorems. Included in this chapter is material concerning linear functionals, continuity, and boundedness. The second chapter contains the proofs of three fundamental theorems of linear analysis: the Open Mapping Theorem, the Hahn-Banach Theorem, and the Uniform Boundedness Principle. The third chapter is concerned with applying some of the results established in earlier chapters. In particular, the concepts of compact operators and Schauder bases are introduced, and a proof that an operator is compact if and only if its adjoint is compact is included. This chapter concludes with a proof of an important application of the Open Mapping Theorem, namely, the Closed Graph Theorem.

A Conjectura de Bateman-Horn dá condições sobre uma família de polinômios com coeficientes inteiros $f_1(X),\\dots,f_k(X)$ para que hajam infinitos $n \\in \\N$ tais que $f_1(n),\\dots,f_k(n)$ sejam todos primos, e determina qual deve ser o comportamento assintótico de tais inteiros $n$. Neste texto, vamos estudar essa conjectura, assim como um método desenvolvido por Solomon W. Golomb que pode ser usado para demonstrá-la. Veremos que esse cálculo prova a Conjectura de Bateman-Horn a menos da troca de um limite com uma série infinita, que é o único passo ainda não provado desse método. Também estudaremos uma tentativa para solucionar esse problema por meio do uso de teoremas abelianos de regularidade, e provaremos que teoremas tão gerais não são suficientes para provar a troca do limite com a série. / Given a family of polynomials with integer coefficients $f_1(X),\\dots,f_k(X)$, one would like to answer the following question: does there exist infinitely many $n \\in \\N$ such that $f_1(n),\\dots,f_k(n)$ are all primes? Schinzel conjectured that if these polynomials satisfy certain simple conditions, then the answer to this question is affirmative. Assuming these conditions, Bateman and Horn proposed a formula for the asymptotic density of the integers $n \\in \\N$ such that $f_1(n),\\dots,f_k(n)$ are all primes. In this text, we shall study the Bateman-Horn Conjecture, as well as a method proposed by Solomon W. Golomb that may be used to prove this conjecture. We shall see that Golomb\'s $\\Lambda$-method would prove the Bateman-Horn Conjecture, except for a single unproved step, namely, the commutation of a limit with an infinite series.

We consider second and third order limit theorems--namely central-limit theorems, Berry-Esseen bounds and concentration inequalities-- and extend them for "symmetric" random objects, and general estimators of exchangeable structures. At first, we consider random processes whose distribution satisfies a symmetry property. Examples include exchangeability, stationarity, and various others. We show that, under a suitable mixing condition, estimates computed as ergodic averages of such processes satisfy a central limit theorem, a Berry-Esseen bound, and a concentration inequality. These are generalized further to triangular arrays, to a class of generalized U-statistics, and to a form of random censoring. As applications, we obtain new results on exchangeability, and on estimation in random fields and certain network model; extend results on graphon models; give a simpler proof of a recent central limit theorem for marked point processes; and establish asymptotic normality of the empirical entropy of a large class of processes. In certain special cases, we recover well-known properties, which can hence be interpreted as a direct consequence of symmetry. The proofs adapt Stein's method. Subsequently, we consider a sequence of-potentially random-functions evaluated along a sequence of exchangeable structures. We show that, under general stability conditions, those values are asymptotically normal. Those conditions are vaguely reminiscent of those familiar from concentration results, however not identical. We require that the output of the functions does not vary significantly when an entry is disturbed; and the size of this variation should not depend markedly on the other entries. Our result generalizes a number of known results, and as corollaries, we obtain new results for several applications: For randomly sub-sampled subgraphs; for risk estimates obtained by K-fold cross validation; and for the empirical risk of double bagging algorithms. The proof adapts the martingale central-limit theorem.

Neste trabalho, provamos um caso particular do Teorema de Ratner de classificação de medidas, que nos diz que se X =&Gamma;\\G é um espaço homogêneo, onde G é um grupo de Lie e &Gamma; é um lattice de G, então dado um subgrupo unipotente U de G, conseguimos classificar as medidas ergódicas com relação a ação por translação do grupo U em X. Além do Teorema de Ratner de classificação de medidas, falamos sobre o Teorema de Ratner de equidistribuição e o Teorema de Ratner do fecho da órbita, que nos dizem como são as órbitas pela ação por translação do grupo U e como é sua dinâmica em X, do ponto de vista da Teoria Ergódica. Embora estes últimos resultados não sejam provados nesta dissertação, exibimos uma importante aplicação do Teorema de Ratner do fecho da órbita em teoria dos números, provando a Conjectura de Oppeinheim, também conhecida como Teorema de Margullis. / In this work, we prove a particular case of the Ratners measure classification theorem, which tell us that if X = &Gamma;\\G is an homogeneous space, where G is a Lie group and &Gamma; is a lattice of G, then given any unipotent group U of G, we can classify the measures that are ergodic with respect to the translation group action of U in X In addition to the Ratners measure classification theorem, we talk about the Ratners equidistribuition theorem and the Ratners orbit closure theorem, which tell us how the orbit due the action by translation by the group U are and how the dynamics in X is, in an Ergodic Theory point of view. While we didnt prove the last two Ratners theorems, we exhibit an important application of the Ratners orbit closure theorem in number theory, proving the Oppeinheim Conjecture, also know as Margullis Theorem.