This dissertation presents new numerical methods for the solution of fractional differential equations of single and distributed order that find application in the different fields of physics and engineering. We start by presenting the relationship between fractional derivatives and processes like anomalous diffusion, and, we then develop new numerical methods for the solution of the time-fractional diffusion equations. The first numerical method is developed for the solution of the fractional diffusion equations with Neumann boundary conditions and the diffusivity parameter depending on the space variable. The method is based on finite differences, and, we prove its convergence (convergence order of O(Δx² + Δt²^-α), 0 < α < 1) and stability. We also present a brief description of the application of such boundary conditions and fractional model to real world problems (heat flux in human skin). A discussion on the common substitution of the classical derivative by a fractional derivative is also performed, using as an example the temperature equation. Numerical methods for the solution of fractional differential equations are more difficult to develop when compared to the classical integer-order case, and, this is due to potential singularities of the solution and to the nonlocal properties of the fractional differential operators that lead to numerical methods that are computationally demanding. We then study a more complex type of equations: distributed order fractional differential equations where we intend to overcome the second problem on the numerical approximation of fractional differential equations mentioned above. These equations allow the modelling of more complex anomalous diffusion processes, and can be viewed as a continuous sum of weighted fractional derivatives. Since the numerical solution of distributed order fractional differential equations based on finite differences is very time consuming, we develop a new numerical method for the solution of the distributed order fractional differential equations based on Chebyshev polynomials and present for the first time a detailed study on the convergence of the method. The third numerical method proposed in this thesis aims to overcome both problems on the numerical approximation of fractional differential equations. We start by solving the problem of potential singularities in the solution by presenting a method based on a non-polynomial approximation of the solution. We use the method of lines for the numerical approximation of the fractional diffusion equation, by proceeding in two separate steps: first, spatial derivatives are approximated using finite differences; second, the resulting system of semi-discrete ordinary differential equations in the initial value variable is integrated in time with a non-polynomial collocation method. This numerical method is further improved by considering graded meshes and an hybrid approximation of the solution by considering a non-polynomial approximation in the first sub-interval which contains the origin in time (the point where the solution may be singular) and a polynomial approximation in the remaining intervals. This way we obtain a method that allows a faster numerical solution of fractional differential equations (than the method obtained with non-polynomial approximation) and also takes into account the potential singularity of the solution. The thesis ends with the main conclusions and a discussion on the main topics presented along the text, together with a proposal of future work.

In recent decades, significant interest, based on physics and engineering applications, has developed on so-called anomalous diffusion processes that possess different spread functions with classical ones. The resulting differential equation whose fundamental solution matches this decay process is best modeled by an equation containing a fractional order derivative. This dissertation mainly focuses on some inverse problems for fractional diffusion equations. After some background introductions and preliminaries in Section 1 and 2, in the third section we consider our first inverse boundary problem. This is where an unknown boundary condition is to be determined from overposed data in a time- fractional diffusion equation. Based upon the fundamental solution in free space, we derive a representation for the unknown parameters as the solution of a nonlinear Volterra integral equation of second kind with a weakly singular kernel. We are able to make physically reasonable assumptions on our constraining functions (initial and given boundary values) to be able to prove a uniqueness and reconstruction result. This is achieved by an iterative process and is an immediate result of applying a certain fixed point theorem. Numerical examples are presented to illustrate the validity and effectiveness of the proposed method. In the fourth section a reaction-diffusion problem with an unknown nonlinear source function, which has to be determined from overposed data, is considered. A uniqueness result is proved and a numerical algorithm including convergence analysis under some physically reasonable assumptions is presented in the one-dimensional case. To show effectiveness of the proposed method, some results of numerical simulations are presented. In Section 5, we also attempted to reconstruct a nonlinear source in a heat equation from a number of known input sources. This represents a new research even for the case of classical diffusion and would be the first step in a solution method for the fractional diffusion case. While analytic work is still in progress on this problem, Newton and Quasi-Newton method are applied to show the feasibility of numerical reconstructions. In conclusion, the fractional diffusion equations have some different properties with the classical ones but there are some similarities between them. The classical tools like integral equations and fixed point theory still hold under slightly different assumptions. Inverse problems for fractional diffusion equations have applications in many engineering and physics areas such as material design, porous media. They are trickier than classical ones but there are also some advantages due to the mildly ill-conditioned singularity caused by the new kernel functions.

Abstract The dissertation considers the time fractional diffusion equation (TFDE) with the Dirichlet boundary condition in the sub-diffusion case, i.e. the order of the time derivative is α ∈ (0,1). In the thesis we have studied the solvability of TFDE by the method of layer potentials. We have shown that both the single layer potential and the double layer potential approaches lead to integral equations which are uniquely solvable. The dissertation consists of four articles and a summary section. The first article presents the solution for the time fractional diffusion equation in terms of the single layer potential. In the second and third article we have studied the boundary behaviour of the layer potentials for TFDE. The fourth paper considers the spline collocation method to solve the boundary integral equation related to TFDE. In the summary part we have proved that TFDE has a unique solution and the solution is given by the double layer potential when the lateral boundary of a bounded domain admits C1 regularity. Also, we have proved that the solution depends continuously on the datum in the sense that a nontangential maximal function of the solution is norm bounded from above by the datum in L2(ΣT). If the datum belongs to the space H1,α/2(ΣT), we have proved that the nontangential function of the gradient of the solution is norm bounded from above by the datum in H1,α/2(ΣT).

This thesis is split in two different topics. Firstly, we study anomalous transport from kinetic models. Secondly, we consider the equations coming from weak wave turbulence theory and we study them via mean-field limits of finite stochastic particle systems. $\textbf{Anomalous transport from kinetic models.}$ The goal is to understand how fractional diffusion arises from kinetic equations. We explain how fractional diffusion corresponds to anomalous transport and its relation to the classical diffusion equation. In previous works it has been seen that particles systems undergoing free transport and scattering with the media can give rise to fractional phenomena in two cases: firstly, if in the dynamics of the particles there is a heavy-tail equilibrium distribution; and secondly, if the scattering rate is degenerate for small velocities. We use these known results in the literature to study the emergence of fractional phenomena for some particular kinetic equations. Firstly, we study BGK-type equations conserving not only mass (as in previous results), but also momentum and energy. In the hydrodynamic limit we obtain a fractional diffusion equation for the temperature and density making use of the Boussinesq relation and we also demonstrate that with the same rescaling fractional diffusion cannot be derived additionally for the momentum. But considering the case of conservation of mass and momentum only, we do obtain the incompressible Stokes equation with fractional diffusion in the hydrodynamic limit for heavy-tailed equilibria. Secondly, we will study diffusion phenomena arising from transport of energy in an anharmonic chain. More precisely, we will consider the so-called FPU-$\beta$ chain, which is a very simple model for a one-dimensional crystal in which atoms are coupled to their nearest neighbours by a harmonic potential, weakly perturbed by a nonlinear quartic potential. The starting point of our mathematical analysis is a kinetic equation; lattice vibrations, responsible for heat transport, are modelled by an interacting gas of phonons whose evolution is described by the Boltzmann Phonon Equation. Our main result is the derivation of an anomalous diffusion equation for the temperature. $\textbf{Weak wave turbulence theory and mean-field limits for stochastic particle systems.}$ The isotropic 4-wave kinetic equation is considered in its weak formulation using model homogeneous kernels. Existence and uniqueness of solutions is proven in a particular setting. We also consider finite stochastic particle systems undergoing instantaneous coagulation-fragmentation phenomena and give conditions in which this system approximates the solution of the equation (mean-field limit).

Fractional diffusion equations have played an increasingly important role in ex- plaining long-range interactions, nonlocal dynamics and anomalous diffusion, pro- viding effective means of describing the memory and hereditary properties of such processes. This dissertation explores the uncertainty propagation in space fractional diffusion equations in one and multiple dimensions with variable diffusivity and order parameters. This is achieved by:(i) deploying accurate numerical schemes of the forward problem, and (ii) employing uncertainty quantifications tools that accelerate the inverse problem. We begin by focusing on parameter calibration of a variable- diffusivity fractional diffusion model. A random, spatially-varying diffusivity field is considered together with an uncertain but spatially homogeneous fractional operator order. Polynomial chaos (PC) techniques are used to express the dependence of the stochastic solution on these random variables. A non-intrusive methodology is used, and a deterministic finite-difference solver of the fractional diffusion model is utilized for this purpose. The surrogates are first used to assess the sensitivity of quantities of interest (QoIs) to uncertain inputs and to examine their statistics. In particular, the analysis indicates that the fractional order has a dominant effect on the variance of the QoIs considered. The PC surrogates are further exploited to calibrate the uncertain parameters using a Bayesian methodology. In the broad range of parameters addressed, the analysis shows that the uncertain parameters having a significant impact on the variance of the solution can be reliably inferred, even from limited observations. Next, we address the numerical challenges when multidimensional space-fractional diffusion equations have spatially varying diffusivity and fractional order. Significant computational challenges arise due to the kernel singularity in the fractional integral operator as well as the resulting dense discretized operators. Hence, we present a singularity-aware discretization scheme that regularizes the singular integrals through a singularity subtraction technique adapted to the spatial variability of diffusivity and fractional order. This regularization strategy is conveniently formulated as a sparse matrix correction that is added to the dense operator, and is applicable to different formulations of fractional diffusion equations. Numerical results show that the singularity treatment is robust, substantially reduces discretization errors, and attains the first-order convergence rate allowed by the regularity of the solutions. In the last part, we explore the application of a Bayesian formalism to detect an anomaly in a fractional medium. Specifically, a computational method is presented for inferring the location and properties of an inclusion inside a two-dimensional domain. The anomaly is assumed to have known shape, but unknown diffusivity and fractional order parameters, and is assumed to be embedded in a fractional medium of known fractional properties. To detect the presence of the anomaly, the medium is forced using a collection of localized sources, and its response is measured at the source locations. To this end, the singularity-aware finite-difference scheme is applied. A non-intrusive regression approach is used to explore the dependence of the computed signals on the properties of the anomaly, and the resulting surrogates are first exploited to characterize the variability of the response, and then used to accelerate the Bayesian inference of the anomaly. In the regime of parameters considered, the computational results indicate that robust estimates of the location and fractional properties of the anomaly can be obtained, and that these estimates become sharper when high contrast ratios prevail between the anomaly and the surrounding matrix.

The discovery of the entropy production paradox (Hoffmann et al., 1998) raised basic questions about the nature of irreversibility in the regime between diffusion and waves. First studied in the form of spatial movements of moments of H functions, pseudo propagation is the pre-limit propagation-like movements of skewed probability density function (PDFs) in the domain between the wave and diffusion equations that goes over to classical partial differential equation propagation of characteristics in the wave limit. Many of the strange properties that occur in this extraordinary regime were thought to be connected in some manner to this form of proto-movement. This paper eliminates pseudo propagation by employing a similar evolution equation that imposes spatial unimodal symmetry on evolving PDFs. Contrary to initial expectations, familiar peculiarities emerge despite the imposed symmetry, but they have a distinct character.

The discovery of the entropy production paradox (Hoffmann et al., 1998) raised basic questions about the nature of irreversibility in the regime between diffusion and waves. First studied in the form of spatial movements of moments of H functions, pseudo propagation is the pre-limit propagation-like movements of skewed probability density function (PDFs) in the domain between the wave and diffusion equations that goes over to classical partial differential equation propagation of characteristics in the wave limit. Many of the strange properties that occur in this extraordinary regime were thought to be connected in some manner to this form of proto-movement. This paper eliminates pseudo propagation by employing a similar evolution equation that imposes spatial unimodal symmetry on evolving PDFs. Contrary to initial expectations, familiar peculiarities emerge despite the imposed symmetry, but they have a distinct character.

Dans cette thèse, nous nous intéressons a la résolution de problèmes de contrôle optimal associés a des équations de diffusion et onde fractionnaires en temps et a données incomplètes, ou les dérivées sont prises au sens de Riemann-Liouville. / In this thesis, we are interested in the résolution of optimal control problems associated to fractional diffusion-wave equations in time with incomplete data, and where derivatives are understood in Riemann-Liouville sense.

abstract: The tools developed for the use of investigating dynamical systems have provided critical understanding to a wide range of physical phenomena. Here these tools are used to gain further insight into scalar transport, and how it is affected by mixing. The aim of this research is to investigate the efficiency of several different partitioning methods which demarcate flow fields into dynamically distinct regions, and the correlation of finite-time statistics from the advection-diffusion equation to these regions. For autonomous systems, invariant manifold theory can be used to separate the system into dynamically distinct regions. Despite there being no equivalent method for nonautonomous systems, a similar analysis can be done. Systems with general time dependencies must resort to using finite-time transport barriers for partitioning; these barriers are the edges of Lagrangian coherent structures (LCS), the analog to the stable and unstable manifolds of invariant manifold theory. Using the coherent structures of a flow to analyze the statistics of trapping, flight, and residence times, the signature of anomalous diffusion are obtained. This research also investigates the use of linear models for approximating the elements of the covariance matrix of nonlinear flows, and then applying the covariance matrix approximation over coherent regions. The first and second-order moments can be used to fully describe an ensemble evolution in linear systems, however there is no direct method for nonlinear systems. The problem is only compounded by the fact that the moments for nonlinear flows typically don't have analytic representations, therefore direct numerical simulations would be needed to obtain the moments throughout the domain. To circumvent these many computations, the nonlinear system is approximated as many linear systems for which analytic expressions for the moments exist. The parameters introduced in the linear models are obtained locally from the nonlinear deformation tensor. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2018

La thèse décrit les propriétés d’équilibre et hors d’équilibre de modèles mathématiques stochastiques de systèmes physiques. À l’aide de simulations numériques, on étudie les fluctuations des différentes quantités mais on s’interesse aussi aux grands déviations dans certains systèmes. La première partie de la thèse se concentre sur l’étude des interfaces rugueuses observées dans des processus de croissance. Ces interfaces sont simulées avec des nouvelles techniques de programmation en parallèle qui nous permettent d’accéder à des systèmes de très grande taille. D’une part, on discute le cas diffusif, représenté par l’équation d’Edward-Wilkinson dans des interfaces périodiques, pour lequel on obtient une solution exacte de l’équation discrète dans l’espace de Fourier. Avec cette solution on déduit le facteur de structure associé aux amplitudes des modes et l’expression exacte est comparée avec les valeurs numériques. De plus, on fait le lien entre les propriétés de premier passage des interfaces et le mouvement Brownien. On mesure la distribution des longueurs des intervalles et on compare les résultats avec une version modifiée du théorème de Sparre-Andersen. D’autre part, on étudie le cas général qui inclut les cas sous-diffusif et superdiffusif avec des conditions de bord périodiques. On étudie pour ces interfaces fractionnaires des propriétés de premier passage liées aux zéros des interfaces. Dans l’état stationnaire, on étudie également les premiers cumulants et propriétés d’échellement de la longueur des intervalles et de la densité de zéros. De plus, on mesure la largeur typique de l’interface et ses propriétés d’échellement. Finalement, on analyse le comportement de ces observables dans les interfaces hors d’équilibre et on discute leur dépendance en la taille du système. On discute également les conditions de stabilité des solutions del’équation discrète, importantes pour les simulations des interfaces. Dans une deuxième partie, on étude la transition de phase dynamique dans des modèles cinétiquement contraints afin d’étudier la transition vitreuse observée dans des verres structuraux. Pour un modèle en dimension un, on étudie la géométrie spatio-temporelle des bulles d’inactivité qui caractérisent les hétérogénéités dynamiques observées dans les verres. On trouve que les directions spatiales et temporelles des bulles ne sont pas liées par un comportement diffusif. En contraste, on confirme l’échellement de l’aire et d’autres quantités attendues pour un système, a priori diffusif. De plus, grâce à la théorie des grandes déviations et l’algorithme de clonage, on identifie la transition de phase dynamique dans des systèmes en deux dimensions spatiales. D’abord on mesure l’énergie libre dynamique pour différentes valeurs du paramètre λ. Après, on conjecture des valeurs critiques λ c = Σ/K, avec Σ la tension surface d’une ı̂le de sites actifs entourée par des sites inactifs dans un modèle effectif et K l’activité moyenne du système, pour laquelle la transition de phase a lieu dans la limite de taille infinie. En mesurant l’activité du système et le nombre d’occupation, on observe la dépendance de ces observables avec la taille des systèmes étudiés loin de la transition. Finalement, on mesure la propagation du front des sites actifs dans tout les systèmes. Pour l’un des systèmes étudiés, on identifie une vitesse balistique du front qui nous permet d’observer la transition de phase d’un point de vue dynamique. / This thesis investigates both equilibrium and nonequilibrium properties of mathematical stochastic models that as a representation of physical systems. By means of extensive numerical simulations we study mean quantities and their fluctuations. Nonetheless, in some systems we are interested also in large deviations. The first part of the thesis focuses on the study of rough interfaces observed in growth processes. These interfaces are simulated with state-of-the-art simulations based on parallel computing which allow us to study very large systems. On the one hand, we discuss the diffusive case given by the Edward-Wilkinson equation in periodic interfaces. For the discrete version of such an equation, we obtain an analytic solution in Fourier space. Fur-ther, we derive an exact expression of the structure factor related with the modes amplitudes describing the interface and compare it with the numerical values. Moreover, using a mapping between stationary interfaces and the Brownian motion, we relate the distribution of the intervals generated by the zeros of the interface with the first-passage distribution given by a the Sparre-Andersen theorem in the case of the Brownian motion. As a generalization of the results obtained in the diffusive case, we study a linear Langevin equation with a Riesz-Feller fractional Laplacian of order z used to simulate sub- and super-diffusive interfaces. In this general case, we identify three regimes based on the scaling behaviour of the cumulants of the intervallengths, the density of zeros and the width of the interface. Finally, we study the evolution in time of some of the observables introduced before. In the second part of the thesis, we study the dynamical phase transition in kinetically constrained models (KCMs) in order to get some insight on the glass transition observed in structural glasses. In a one-dimensional KCM we study the geometry of the bubbles of inactivity in space-time for systems at different temperatures. We find that the spatial length of the bubbles does not scale diffusively with its temporal duration. In contrast, we confirm a vidiffusive behaviour for other quantities studied. Further, by means of large deviation theory and cloning algorithms, we identify the dynamical phase transition in two-dimensional systems. To start with, we measure numerically the dynamical free energy both by measuring the largest eigenvalue of the evolution operator,for small systems, and via the cloning algorithm, for larger systems. We conjecture a value λ c = Σ/K, with Σ the surface tensionof a bubble of activity surrounded by a sea of inactive sites in an effective interfacial model and K the mean activity of the system, for each of the systems studied. For the activity of the system and the occupation number we discuss their scaling properties far from the phase transition. Starting from an empty system subject to different boundary conditions, we investigate the front propagation of active sites. We argue that the phase transition in this case can be identified by the abrupt slowing-down of the front. This is done by measuring the ballistic speed of the front in the simplest case studied. Finally, we propose an effective model following the Feynman-Kac formula for a moving front.-proprietés de premier passage, interface rugueuse, diffusion fractionnaire , système hors d'équilibre, transition de phase dynamique, modèle cinétiquement contraint, grandes déviations.-first-passage properties, rough interface, fractional diffusion, out-of-equilibrium system, dynamical phase transition, kinetically constrained model, large deviations