In this dissertation we describe a coordinate scaling technique for the numerical approximation of solutions to certain problems posed on unbounded domains in two and three dimensions. This technique amounts to introducing variable coefficients into the problem, which results in defining a solution coinciding with the solution to the original problem inside a bounded domain of interest and rapidly decaying outside of it. The decay of the solution to the modified problem allows us to truncate the problem to a bounded domain and subsequently solve the finite element approximation problem on a finite domain. The particular problems that we consider are exterior problems for the Laplace equation and the time-harmonic acoustic and elastic wave scattering problems. We introduce a real scaling change of variables for the Laplace equation and experimentally compare its performance to the performance of the existing alternative approaches for the numerical approximation of this problem. Proceeding from the real scaling transformation, we introduce a version of the perfectly matched layer (PML) absorbing boundary as a complex coordinate shift and apply it to the exterior Helmholtz (acoustic scattering) equation. We outline the analysis of the continuous PML problem, discuss the implementation of a numerical method for its approximation and present computational results illustrating its efficiency. We then discuss in detail the analysis of the elastic wave PML problem and its numerical discretiazation. We show that the continuous problem is well-posed for sufficiently large truncation domain, and the discrete problem is well-posed on the truncated domain for a sufficiently small PML damping parameter. We discuss ways of avoiding the latter restriction. Finally, we consider a new non-spherical scaling for the Laplace and Helmholtz equation. We present computational results with such scalings and conduct numerical experiments coupling real scaling with PML as means to increase the efficiency of the PML techniques, even if the damping parameters are small.

The idea of automatic programming using the genetic programming paradigm is a concept that has been explored in the work of Koza and several works since. Most problems attempted using genetic programming are finite in size, meaning that the problem involved evolving a function that operates over a finite domain, or evolving a routine that will only run for a finite amount of time. For problems with a finite domain, the internal representation of each individual is typically a finite automaton that is unable to store an unbounded amount of data. This thesis will address the problem of applying genetic programming to problems that have a ``discrete unbounded domain", meaning the problem involves evolving a function that operates over an unbounded domain with discrete quantities. For problems with an discrete unbounded domain, the range of possible behaviors achievable by the evolved functions increases with more versatile internal memory schemes for each of the individuals. The specific problem that I will address in this thesis is the problem of evolving a real-time deciding program for a fixed language of strings. I will discuss two paradigms that I will use to attempt this problem. Each of the paradigms will allow each individual to store an unbounded amount of data, using an internal memory scheme with at least the capabilities of a Turing tape. As each character of an input string is being processed in real time, the individual will be able to imitate a single step of a Turing machine. While the real-time restriction will certainly limit the languages for which a decider may be evolved, the fact that the evolved deciding programs run in real-time yields possible applications for these paradigms in the discovery of new algorithms. The first paradigm that I will explore will take a naive approach that will ultimately prove to be unsuccessful. The second paradigm that I will explore will take a more careful approach that will have a much greater success, and will provide insight into the design of genetic programming paradigms for problems over a discrete unbounded domain.

The idea of automatic programming using the genetic programming paradigm is a concept that has been explored in the work of Koza and several works since. Most problems attempted using genetic programming are finite in size, meaning that the problem involved evolving a function that operates over a finite domain, or evolving a routine that will only run for a finite amount of time. For problems with a finite domain, the internal representation of each individual is typically a finite automaton that is unable to store an unbounded amount of data. This thesis will address the problem of applying genetic programming to problems that have a ``discrete unbounded domain", meaning the problem involves evolving a function that operates over an unbounded domain with discrete quantities. For problems with an discrete unbounded domain, the range of possible behaviors achievable by the evolved functions increases with more versatile internal memory schemes for each of the individuals. The specific problem that I will address in this thesis is the problem of evolving a real-time deciding program for a fixed language of strings. I will discuss two paradigms that I will use to attempt this problem. Each of the paradigms will allow each individual to store an unbounded amount of data, using an internal memory scheme with at least the capabilities of a Turing tape. As each character of an input string is being processed in real time, the individual will be able to imitate a single step of a Turing machine. While the real-time restriction will certainly limit the languages for which a decider may be evolved, the fact that the evolved deciding programs run in real-time yields possible applications for these paradigms in the discovery of new algorithms. The first paradigm that I will explore will take a naive approach that will ultimately prove to be unsuccessful. The second paradigm that I will explore will take a more careful approach that will have a much greater success, and will provide insight into the design of genetic programming paradigms for problems over a discrete unbounded domain.

Unbounded domains often appear in engineering applications, such as acoustic or elastic wave radiation from a body immersed in an infinite medium. To simulate the unboundedness of the domain special boundary conditions have to be imposed: the Sommerfeld radiation condition. In the present work we focused on steady-state wave propagation. The objective of this research is to obtain accurate prediction of phenomena occurring in exterior acoustics and elastodynamics and ensure the quality of the solutions even for high wavenumbers. To achieve this aim, we develop higher-order domain-based schemes: Spectral Element Method (SEM) coupled to Dirichlet-to-Neumann (DtN ), Perfectly Matched Layer (PML) and Infinite Element (IEM) methods. Spectral elements combine the rapid convergence rates of spectral methods with the geometric flexibility of the classical finite element methods. The interpolation is based on Chebyshev and Legendre polynomials. This work presents an implementation of these techniques and their validation exploiting some benchmark problems. A detailed comparison between the DtN, PML and IEM is made in terms of accuracy and convergence, conditioning and computational cost.

We study asymptotic properties of evolution partial differential equations posed in unbounded spatial domain in the context of locally uniform spaces. This context allows the use of non-integrable data and carries an inherent non-compactness and non-separability. We establish the existence of a lo- cally compact attractor for non-local parabolic equation and weakly damped semilinear wave equation and provide an upper bound on the Kolmogorov's ε-entropy of these attractors and the attractor of strongly damped wave equation in the subcritical case using the method of trajectories. Finally we also investigate infinite dimensional exponential attractors of nonlinear reaction-diffusion equation in its natural energy setting. 1