For many combinatorial objects we can associate a natural probability distribution on the members of the class, and we can then call the resulting class a class of random structures. Random structures form good models of many real world problems, in particular real networks and disordered media. For many such problems, the systems under consideration can be very large, and we often care about whether a property holds most of the time. In particular, for a given class of random structures, we say that a property holds with high probability if the probability that that property holds tends to one as the size of the structures increase. We examine several classes of random structures with real world applications, and look at some properties of each that hold with high probability. First we look at percolation in 3 dimensional lattices, giving a method for producing rigorous confidence intervals on the percolation threshold. Next we look at random geometric graphs, first examining the connectivity thresholds of nearest neighbour models, giving good bounds on the threshold for a new variation on these models useful for modelling wireless networks, and then look at the cop number of the Gilbert model. Finally we look at the structure of random sum-free sets, in particular examining what the possible densities of such sets are, what substructures they can contain, and what superstructures they belong to.

This thesis studies the geometry of objects from 2-dimensional statistical physics in the continuum. Chapter 1 is an introduction to Schramm-Loewner evolutions (SLE). SLEs are the canonical family of non-self-intersecting, conformally invariant random curves with a domain-Markov property. The family is indexed by a parameter, usually denoted by κ, which controls the regularity of the curve. We give the definition of the SLEκ process, and summarise the proofs of some of its properties. We give particular attention to the Rohde-Schramm theorem which, in broad terms, tells us that an SLEκ is a curve. In Chapter 2 we introduce the Gaussian free field (GFF), a conformally invariant random surface with a domain-Markov property. We explain how to couple the GFF and an SLEκ process, in particular how a GFF can be unzipped along a reverse SLEκ to produce another GFF. We also look at how the GFF is used to define Liouville quantum gravity (LQG) surfaces, and how thick points of the GFF relate to the quantum gravity measure. Chapter 3 introduces a diffusion on LQG surfaces, the Liouville Brownian motion (LBM). The main goal of the chapter is to complete an estimate given by N. Berestycki, which gives an upper bound for the Hausdor dimension of times that a γ-LBM spends in α-thick points for γ, α ∈ [0, 2). We prove the corresponding, tight, lower bound. In Chapter 4 we give a new proof of the Rohde-Schramm theorem (which tells us that an SLEκ is a curve), which is valid for all values of κ except κ = 8. Our proof uses the coupling of the reverse SLEκ with the free boundary GFF to bound the derivative of the inverse of the Loewner flow close to the origin. Our knowledge of the structure of the GFF lets us find bounds which are tight enough to ensure continuity of the SLEκ trace.

We study a new method for the strong approximate solution of stochastic differential equations using coupling and we prove order one error bounds for the new scheme in Lp space assuming the invertibility of the diffusion matrix. We introduce and implement two couplings called the exact and approximate coupling for this scheme obtaining good agreement with the theoretical bound. Also we describe a method for non-invertibility case (Combined method) and we investigate its convergence order which will give O(h3/4 √log(h)j) under some conditions. Moreover we compare the computational results for the combined method with its theoretical error bound and we have obtained a good agreement between them. In the last part of this thesis we work out the performance of the multilevel Monte Carlo method using the new scheme with the exact coupling and we compare the results with the trivial coupling for the same scheme.

There is a good deal of uncertainty and sensitivity in the results for wave impact. In a practical situation, many parameters such as the wave climate will not be known with any accuracy especially the frequency and severity of wave breaking. Even if the wave spectrum is known, this is usually recorded offshore, requiring same sort of (linear) transfer function to estimate the wave climate at the seawall. What is more, the higher spectral moments will generally be unknown. Wave breaking, according to linear wave theory, is known to depend on the wave spectrum, see Srokosz (1986) and Greenhow (1989). Not only is the wave climate unknown, but the aeration of the water will also be subject to uncertainty. This affects rather dramatically the speed of sound in the water/bubble mixture and hence the value of the acoustic pressure that acts as a maximum cutoff for pressure calculated by any incompressible model. The results are also highly sensitive to the angle of alignment of the wave front and seawall. Here we consider the worst case scenario of perfect alignment. Given the above, it seems sensible to exploit the simple pressure impulse model used in this thesis. Thus Cooker (1990) proposed using the pressure impulse P(x, y) that is the time integral of the pressure over the duration of the impact. This results in a simplified, but much more stable, model of wave impact on the coastal structures, and forms the basis of this thesis, as follows: Chapter 1 is an overview about this topic, a brief summary of the work which will follow and a summary of the contribution of this thesis. Chapter 2 gives a literature review of wave impact, theoretically and experimentally. The topics covered include total impulse, moment impulse and overtopping. A summary of the present state of the theory and Cooker’s model is also presented in Chapter 2. In Chapter 3 and Chapter 4, we extend the work of Greenhow (2006). He studied the berm and ditch problems, see Chapter 3, and the missing block problem in Chapter 4, and solved the problems by using a basis function method. I solve these problems in nondimensionlised variables by using a hybrid collocation method in Chapter 3 and by using the same method as Greenhow (2006) in Chapter 4. The works are extended by calculating the total impulse and moment impulse, and the maximum pressure arising from the wave impact for each problem. These quantities will be very helpful from a practical point of view for engineers and designers of seawalls. The mathematical equations governing the fluid motion and its boundary conditions are presented. The deck problem together with the mathematical formulation and boundary conditions for the problem is presented in Chapters 5 and 6 by using a hybrid collocation method. For this case, the basis function method fails due to hyperbolic terms in these formulations growing exponentially. The formulations also include a secular term, not present in Cooker’s formulation. For Chapter 5, the wave hits the wall in a horizontal direction and for Chapter 6, the wave hits beneath the deck in a vertical direction. These problems are important for offshore structures where providing adequate freeboard for decks contributes very significantly to the cost of the structure. Chapter 7 looks at what happens when we have a vertical baffle. The mathematical formulation and the boundary conditions for four cases of baffles which have different positions are presented in this chapter. We use a basis function method to solve the mathematical formulation, and total impulse and moment impulse are investigated for each problem. These problems are not, perhaps, very relevant to coastal structures. However, they are pertinent to wave impacts in sloshing tanks where baffles are used to detune the natural tank frequencies away from environmental driving frequencies (e.g ship roll due to wave action) and to damp the oscillations by shedding vortices. They also provide useful information for the design of oscillating water column wave energy devices. Finally, conclusions from the research and recommendations for future work are presented in Chapter 8.

Experimental studies have shown that the protein abundance in living cells varies from few tens to several thousands molecules per species. Molecular fluctuations roughly scale as the inverse square root of the number of molecules due to the random timing of reactions. It is hence expected that intrinsic noise plays an important role in the dynamics of biochemical networks. The Chemical Master Equation is the accepted description of these systems under well-mixed conditions. Because analytical solutions to this equation are available only for simple systems, one often has to resort to approximation methods. A popular technique is an expansion in the inverse volume to which the reactants are confined, called van Kampen's system size expansion. Its leading order terms are given by the phenomenological rate equations and the linear noise approximation that quantify the mean concentrations and the Gaussian fluctuations about them, respectively. While these approximations are valid in the limit of large molecule numbers, it is known that physiological conditions often imply low molecule numbers. We here develop systematic approximation methods based on higher terms in the system size expansion for general biochemical networks. We present an asymptotic series for the moments of the Chemical Master Equation that can be computed to arbitrary precision in the system size expansion. We then derive an analytical approximation of the corresponding time-dependent probability distribution. Finally, we devise a diagrammatic technique based on the path-integral method that allows to compute time-correlation functions. We show through the use of biological examples that the first few terms of the expansion yield accurate approximations even for low number of molecules. The theory is hence expected to closely resemble the outcomes of single cell experiments.

L’objet de cette thèse concerne l’étude asymptotique des processus de branchement sur-critiques en environnement aléatoire, qui sont une généralisation du processus de Galton-Watson, avec une loi de reproduction choisie aléatoirement et de manière i.i.d. suivant les générations. Dans le cas de non extinction, nous démontrons une succession de résultats asymptotiques plus fins que ceux établis dans des travaux antérieurs. Le chapitre 1 est consacré à l’étude de l’écart relatif entre le processus (Zn) normalisé et la loi normale. Nous établissons une borne de type Berry-Esseen ainsi qu’un développement pour des déviations de type Cramér, généralisant ainsi le théorème central limite et le principe des déviations modérées établis précédemment dans la littérature. Le second chapitre concerne l'asymptotique de la distribution du processus (Zn) ainsi que le moment harmonique critique de la variable limite W de la population normalisée. Nous établissons un équivalent de l'asymptotique de la distribution du processus Zn et donnons une caractérisation des constantes via une équation fonctionnelle similaire au cas du processus de Galton-Watson. Dans le cas des processus de branchement en environnement aléatoire, les résultats améliorent l'équivalent asymptotique de la distribution de Zn établi dans des travaux antérieurs sous normalisation logarithmique, sous la condition que chaque individu donne naissance à au moins un individu. Nous déterminons aussi la valeur critique pour l'existence du moment harmonique de W sous des conditions simples d'existence de moments, qui sont bien plus faibles que les hypothèses imposées dans la littérature, et généralisons le résultat à Z_0=k individus initiaux. Le troisième chapitre est consacré à l'étude de l'asymptotique des moments harmoniques d'ordre r>0 de Zn. Nous établissons un équivalent et donnons une expression des constantes. Le résultat met en évidence un phénomène de transition de phase, relié aux transitions de phase des grandes déviations inférieures du processus (Zn). En application de ce résultat, nous établissons un résultat de grandes déviations inférieures pour le processus (Zn) sous des hypothèses plus faibles que celles imposées dans des travaux précédents. Nous améliorons également la vitesse de convergence dans un théorème central limite vérifié par W_n-W, et déterminons l'asymptotique de la probabilité de grandes déviations pour le ratio Zn+1/Z_n. / The purpose of this Ph.D. thesis is the study of branching processes in a random environment, say (Z_n), which are a generalization of the Galton-Watson process, with the reproduction law chosen randomly in each generation in an i.i.d. manner. We consider the case of a supercritical process, assuming the condition that each individual gives birth to at least one child. The first part of this work is devoted to the study of the relative and absolute distance between the normalized process log Z_n and the normal law. We show a Berry-Esseen bound and establish a Cramér type large deviation expansion, which generalize the central limit theorem and the moderate deviation principle established for log Z_n in previous studies.In the second chapter we study the asymptotic of the distribution of Z_n, and the critical value for the existence of harmonic moments of the limit variable W of the normalized population size. We give an equivalent of the asymptotic distribution of Z_n and characterize the constants by a functional relation which is similar to that obtained for a Galton-Watson process. For a branching process in a random environment, our result generalizes the equivalent of the asymptotic distribution of Z_n established in a previous work in a log-scale, under the condition that each individual gives birth to at least one child. We also characterize the critical value for the existence of harmonic moments of the limit variable W under weaker conditions that in previous studies and generalize this result for processes starting with Z_0=k initial individuals. The third chapter is devoted to the study of the asymptotic of the harmonic moments of order r>0 of Z_n. We show the exact decay rate and give an expression of the limiting constants. The result reveals a phase transition phenomenon which is linked to the phase transitions in the lower large deviations established in earlier studies. As an application, we improve a lower large deviation result for the process (Z_n) under weaker hypothesis than those stated in the literature. Moreover, we also improve the rate of convergence in a central limit theorem for W-W_n and give the asymptotic of the large deviation for the ratio Zn+1/Z_n.

In this work we present some new results concerning stochastic partial differential and integro-differential equations (SPDEs and SPIDEs) that appear in non-linear filtering. We prove existence and uniqueness of solutions of SPIDEs, we give a comparison principle and we suggest an approximation scheme for the non-local integral operators. Regarding SPDEs, we use techniques motivated by the work of De Giorgi, Nash, and Moser, in order to derive global and local supremum estimates, and a weak Harnack inequality.

The purpose of this thesis is to develop techniques for analysing interacting particle systems on the half-line. When the number of particles becomes large, stochastic partial differential equations (SPDEs) with Dirichlet boundary conditions will be the natural objects for describing the dynamics of the population's empirical measure. As a source of motivation, we consider systems that arise naturally as models for the pricing of portfolio credit derivatives, although similar applications are found in mathematical neuroscience, stochastic filtering and mean-field games. We will focus on a stochastic McKean--Vlasov system in which a collection of Brownian motions interact through a correlation which is a function of the proportion of particles that have been absorbed at level zero. We prove a law of large numbers where the limiting object is the unique solution to (the weak formulation of) the loss-dependent SPDE: dV_t(x) = 1/2 &part;_xxV_t(x)dt - p(L_t)&part;_xV_t(x)dW_t, V_t(0)=0, where L_t = 1-&lmoust;^&infin;<sub style='position: relative; left: -.8em;'>t</sub></sup>V_t(x)dx, V is a density process on the half-line and W is a Brownian motion. The correlation function is assumed to be piecewise Lipschitz, which encompasses a natural class of credit models. The first of our theoretical developments is to introduce the kernel smoothing method in the dual of the first Sobolev space, H^-1, with the aim of proving uniqueness results for SPDEs. A benefit of this approach is that only first order moment estimates of solutions are required, and in the particle setting this translates into studying the particles at an individual level rather than as a correlated collection. The second idea is to extend Skorokhod's M₁ topology to the space of processes that take values in the tempered distributions. The benefit we gain is that monotone functions have zero modulus of continuity under this topology, so the loss process, L, is easy to control. As a final example, we consider the fluctuations in the convergence of a basic particle system with constant correlation. This gives rise to a central limit theorem, for which the limiting object is a solution to an SPDE with random transport and an additive idiosyncratic driver acting on the first derivative terms. Conditional on the systemic random variables, this driver is a space-time white noise with intensity controlled by the empirical measure of the underlying system. The SPDE has insufficient regularity for us to work in any Sobolev space higher than H^-1, hence we have an example of where our extension to the kernel smoothing method is necessary.

Probability theory provides a mathematically rigorous yet conceptually flexible calculus of uncertainty, allowing the construction of complex hierarchical models for real-world inference tasks. Unfortunately, exact inference in probabilistic models is often computationally expensive or even intractable. A close inspection in such situations often reveals that computational bottlenecks are confined to certain aspects of the model, which can be circumvented by approximations without having to sacrifice the model's interesting aspects. The conceptual framework of graphical models provides an elegant means of representing probabilistic models and deriving both exact and approximate inference algorithms in terms of local computations. This makes graphical models an ideal aid in the development of generalizable approximations. This thesis contains a brief introduction to approximate inference in graphical models (Chapter 2), followed by three extensive case studies in which approximate inference algorithms are developed for challenging applied inference problems. Chapter 3 derives the first probabilistic game tree search algorithm. Chapter 4 provides a novel expressive model for inference in psychometric questionnaires. Chapter 5 develops a model for the topics of large corpora of text documents, conditional on document metadata, with a focus on computational speed. In each case, graphical models help in two important ways: They first provide important structural insight into the problem; and then suggest practical approximations to the exact probabilistic solution.

This thesis is devoted to the study of excitations in atomic and polariton Bose-Einstein condensates (BEC). These two specimens are prime examples for equilibrium and non equilibrium BEC. The corresponding condensate wave function of each system satisfies a particular partial differential equation (PDE). These PDEs are discussed in the beginning of this thesis and justified in the context of the quantum many-body problem. For high occupation numbers and when neglecting quantum fluctuations the quantum field operator simplifies to a semiclassical wave. It turns out that the interparticle interactions can be simplified to a single parameter, the scattering length, which gives rise to an effective potential and introduces a nonlinearity to the PDE. In both cases, i.e. equilibrium and non equilibrium, the main model corresponding to the semiclassical wave is the Gross-Pitaevskii equation (GPE), which includes certain mathematical adaptions depending on the physical context of the consideration and the nature of particles/quasiparticles, such as additional complex pumping and growth terms or terms due to motion. In the course of this work I apply a variety of state-of-the-art analytical and numerical tools to gain information about these semiclassical waves. The analytical tools allow e.g. to determine the position of the maximum density of the condensate wave function or to find the critical velocities at which excitations are expected to be generated within the condensate. In addition to analytical considerations I approximate the GPE numerically. This allows to gain the condensate wave function explicitly and is often a convenient tool to study the emergence of excitations in BEC. It is in particular shown that the form of the possible excitations significantly depends on the dimensionality of the considered system. The generated excitations within the BEC include quantum vortices, quantum vortex rings or solitons. In addition multicomponent systems are considered, which enable more complex dynamical scenarios. Under certain conditions imposed on the condensate one obtains dark-bright soliton trains within the condensate wave function. This is shown numerically and analytical expressions are found as well. In the end of this thesis I present results as part of an collaborative effort with a group of experimenters. Here it is shown that the wave function due to a complex GPE fits well with experiments made on polariton condensates, statically and dynamically.