We describe the large-time moment asymptotics for the parabolic Anderson model where the speed of the diffusion is coupled with time, inducing an acceleration or deceleration. We find a lower critical scale, below which the mass flow gets stuck. On this scale, a new interesting variational problem arises in the description of the asymptotics. Furthermore, we find an upper critical scale above which the potential enters the asymptotics only via some average, but not via its extreme values. We make out altogether five phases, three of which can be described by results that are qualitatively similar to those from the constant-speed parabolic Anderson model in earlier work by various authors. Our proofs consist of adaptations and refinements of their methods, as well as a variational convergence method borrowed from finite elements theory.

An ever increasing demand for instant and reliable information on modern communication networks forces codewords to operate in a non-asymptotic regime. To achieve reliability for imperfect channels in this regime, codewords need to be retransmitted from receiver to the transmit buffer, aided by a fast feedback mechanism. Large occupancy of this buffer results in longer communication delays. Therefore, codewords need to be designed carefully to reduce transmit queue-length and thus the delay experienced in this buffer. We first study the consequences of physical layer decisions on the transmit buffer occupancy. We develop an analytical framework to relate physical layer channel to the transmit buffer occupancy. We compute the optimal code-rate for finite-length codewords operating over a correlated channel, under certain communication service guarantees. We show that channel memory has a significant impact on this optimal code-rate. Next, we study the delay in small ad-hoc networks. In particular, we find out what rates can be supported on a small network, when each flow has a certain end-to-end service guarantee. To this end, service guarantee at each intermediate link is characterized. These results are applied to study the potential benefits of setting up a network suitable for network coding in multicast. In particular, we quantify the gains of network coding over classic routing for service provisioned multicast communication over butterfly networks. In the wireless setting, we study the trade-off between communications gains achieved by network coding and the cost to set-up a network enabling network coding. In particular, we show existence of scenarios where one should not attempt to create a network suitable for coding. Insights obtained from these studies are applied to design a distributed rate control algorithm in a large network. This algorithm maximizes sum-utility of all flows, while satisfying per-flow end-to-end service guarantees. We introduce a notion of effective-capacity per communication link that captures the service requirements of flows sharing this link. Each link maintains a price and effective-capacity, and each flow maintains rate and dissatisfaction. Flows and links update their respective variables locally, and we show that their decisions drive the system to an optimal point. We implemented our algorithm on a network simulator and studied its convergence behavior on few networks of practical interest.

No description available.

This thesis consists of three parts: The first and second parts focus on long-time asymptotics of macroscopic and kinetic models respectively, while in the third part we connect these regimes using different scaling approaches. (1) Keller–Segel-type aggregation-diffusion equations: We study a Keller–Segel-type model with non-linear power-law diffusion and non-local particle interaction: Does the system admit equilibria? If yes, are they unique? Which solutions converge to them? Can we determine an explicit rate of convergence? To answer these questions, we make use of the special gradient flow structure of the equation and its associated free energy functional for which the overall convexity properties are not known. Special cases of this family of models have been investigated in previous works, and this part of the thesis represents a contribution towards a complete characterisation of the asymptotic behaviour of solutions. (2) Hypocoercivity techniques for a fibre lay-down model: We show existence and uniqueness of a stationary state for a kinetic Fokker-Planck equation modelling the fibre lay-down process in non-woven textile production. Further, we prove convergence to equilibrium with an explicit rate. This part of the thesis is an extension of previous work which considered the case of a stationary conveyor belt. Adding the movement of the belt, the global equilibrium state is not known explicitly and a more general hypocoercivity estimate is needed. Although we focus here on a particular application, this approach can be used for any equation with a similar structure as long as it can be understood as a certain perturbation of a system for which the global Gibbs state is known. (3) Scaling approaches for collective animal behaviour models: We study the multi-scale aspects of self-organised biological aggregations using various scaling techniques. Not many previous studies investigate how the dynamics of the initial models are preserved via these scalings. Firstly, we consider two scaling approaches (parabolic and grazing collision limits) that can be used to reduce a class of non-local kinetic 1D and 2D models to simpler models existing in the literature. Secondly, we investigate how some of the kinetic spatio-temporal patterns are preserved via these scalings using asymptotic preserving numerical methods.

La Géométrie Discrète, comme Science de l'Informatique Théorique, étudie notamment les motifs linéaires tels que les primitives discrètes apparaissant dans les images : les droites discrètes, les segments discrets, les plans discrets, les morceaux de plans discrets par exemple. Dans ce travail, je me concentre tout particulièrement sur les diagrammes de Farey qui apparaissent lors de l'étude des primitives discrètes que sont les (m,n)-cubes, autrement dit les morceaux de plans discrets. J’étudie notamment la Combinatoire des droites formant les diagrammes de Farey, en établissant des formules exactes. Je montre alors que certaines méthodes utilisées auparavant ne permettront pas d'optimiser la Combinatoire des (m,n)-cubes. J'obtiens aussi une estimation asymptotique en utilisant la Théorie des Nombres Combinatoire. Puis, concernant les sommets apparaissant dans les diagrammes de Farey, j'obtiens une borne inférieure. J'analyse alors les stratégies déjà mises en place pour l'étude des $(m,n)$-cubes par les seuls diagrammes de Farey en deux dimensions. Afin d'obtenir de nouvelles bornes plus précises pour les $(m,n)$-cubes, une des seules méthodes actuellement existantes, est de proposer une généralisation de la notion de pré image d'un segment discret, à celle de pré image d'un $(m,n)$-cube, avec pour conséquence une nouvelle inégalité combinatoire sur le cardinal des (m,n)-cubes (inégalité qui pourrait même s'avérer être une égalité). Ainsi, nous introduisons la notion de diagramme de Farey en trois dimensions / Discrete Geometry, as Theoretical Computer Science, studies in particular linear patterns such as discrete primitives in images: the discrete lines, discrete segments, the discrete planes, pieces of discrete planes, for example. In this work, I particularly focused on Farey diagrams that appear in the study of the $ (m, n) $ - cubes, ie the pieces of discrete planes. Among others, I study the Combinatorics of the Farey lines forming diagram Farey, establishing exact formulas. I also get an asymptotic estimate using Combinatorial Number Theory. Then, I get a lower bound for the cardinality of the Farey vertices. After that, we analyze the strategies used in the literature for the study of (m, n)- cubes only by Farey diagrams in two dimensions. In order to get new and more accurate bounds for (m, n)- cubes, one of the few available methods, is to propose a generalization for the concept of preimage of a discrete segment for (m, n) - cube, resulting in a new combinatorial inequality. Thus, we introduce the notion Farey diagram in three dimensions

Ce mémoire contient deux articles que j’ai rédigés au cours de ma maîtrise. Le premier chapitre sert d’introduction à ces articles. Plusieurs concepts de géométrie spectrale y sont présentés dans le contexte du problème de Steklov, en plus des résultats principaux des chapitres subséquents. Le second chapitre porte sur le problème de Steklov paramétrique sur des surfaces lisses. Un développement asymptotique complet des valeurs propres du problème est obtenu à l’aide de méthodes pseudodifférentielles. Celui-ci généralise l’asymptotique spectrale déjà connue du problème de Steklov classique. Nous en déduisons de nouveaux invariants géométriques déterminés par le spectre. Le troisième chapitre porte sur le problème de ballottement sur des prismes à base triangulaire. Le but est de comprendre comment les angles du prisme affectent le deuxième terme du développement asymptotique de la fonction de compte des valeurs propres. En construisant des quasimodes, nous obtenons une expression de ce terme que nous conjecturons comme étant la bonne pour les vraies valeurs propres. Cette conjecture est alors supportée par des expériences numériques. / This thesis contains two articles that I wrote during my M.Sc. studies. The first chapter serves as an introduction to both articles. Some concepts of spectral geometry in the context of the Steklov problem are presented, as well as the main results of the subsequent chapters. The second chapter concerns the parametric Steklov problem on smooth surfaces. We obtain a complete asymptotic expansion of the eigenvalues of the problem by using pseudodifferential techniques. This generalizes the already known spectral asymptotics of the classical Steklov problem. We deduce new geometric invariants determined by the spectrum. The third chapter concerns the sloshing problem on triangular prisms. The goal is to understand how the angles in the prism affect the second term in the asymptotic expansion of the eigenvalue counting function. By constructing quasimodes, we obtain an expression for this term that we conjecture as being correct for the true eigenvalues. This conjecture is then supported by numerical experiments.

Indiana University-Purdue University Indianapolis (IUPUI) / Useful medical indices pose important roles in predicting medical outcomes. Medical indices, such as the well-known Body Mass Index (BMI), Charleson Comorbidity Index, etc., have been used extensively in research and clinical practice, for the quantification of risks in individual patients. However, the development of these indices is challenged; and primarily based on heuristic arguments. Statistically, most medical indices can be expressed as a function of a linear combination of individual variables and fitted by single-index model. Single-index model represents a way to retain latent nonlinear features of the data without the usual complications that come with increased dimensionality. In my dissertation, I propose a single-index model approach to analytically derive indices from observed data; the resulted index inherently correlates with specific health outcomes of interest. The first part of this dissertation discusses the derivation of an index function for the prediction of one outcome using longitudinal data. A cubic-spline estimation scheme for partially linear single-index mixed effect model is proposed to incorporate the within-subject correlations among outcome measures contributed by the same subject. A recursive algorithm based on the optimization of penalized least square estimation equation is derived and is shown to work well in both simulated data and derivation of a new body mass measure for the assessment of hypertension risk in children. The second part of this dissertation extends the single-index model to a multivariate setting. Specifically, a multivariate version of single-index model for longitudinal data is presented. An important feature of the proposed model is the accommodation of both correlations among multivariate outcomes and among the repeated measurements from the same subject via random effects that link the outcomes in a unified modeling structure. A new body mass index measure that simultaneously predicts systolic and diastolic blood pressure in children is illustrated. The final part of this dissertation shows existence, root-n strong consistency and asymptotic normality of the estimators in multivariate single-index model under suitable conditions. These asymptotic results are assessed in finite sample simulation and permit joint inference for all parameters.

No description available.

We describe the large-time moment asymptotics for the parabolic Anderson model where the speed of the diffusion is coupled with time, inducing an acceleration or deceleration. We find a lower critical scale, below which the mass flow gets stuck. On this scale, a new interesting variational problem arises in the description of the asymptotics. Furthermore, we find an upper critical scale above which the potential enters the asymptotics only via some average, but not via its extreme values. We make out altogether five phases, three of which can be described by results that are qualitatively similar to those from the constant-speed parabolic Anderson model in earlier work by various authors. Our proofs consist of adaptations and refinements of their methods, as well as a variational convergence method borrowed from finite elements theory.

Dans cette thèse, nous étudions l'ensemble des solutions d'équations aux dérivées partielles résultant de modèles d'astrophysique et de biologie. Nous répondons aux questions de l'existence, mais aussi nous essayons de décrire le comportement de certaines familles de solutions lorsque les paramètres varient. Tout d'abord, nous étudions deux problèmes issus de l'astrophysique, pour lesquels nous montrons l'existence d'ensembles particuliers de solutions dépendant d'un paramètre à l'aide de la méthode de réduction de Lyapunov-Schmidt. Ensuite un argument de perturbation et le théorème du Point xe de Banach réduisent le problème original à un problème de dimension finie, et qui peut être résolu, habituellement, par des techniques variationnelles. Le reste de la thèse est consacré à l'étude du modèle Keller-Segel, qui décrit le mouvement d'amibes unicellulaires. Dans sa version plus simple, le modèle de Keller-Segel est un système parabolique-elliptique qui partage avec certains modèles gravitationnels la propriété que l'interaction est calculée au moyen d'une équation de Poisson / Newton attractive. Une différence majeure réside dans le fait que le modèle est défini dans un espace bidimensionnel, qui est expérimentalement consistant, tandis que les modèles de gravitationnels sont ordinairement posés en trois dimensions. Pour ce problème, les questions de l'existence sont bien connues, mais le comportement des solutions au cours de l'évolution dans le temps est encore un domaine actif de recherche. Ici nous étendre les propriétés déjà connues dans des régimes particuliers à un intervalle plus large du paramètre de masse, et nous donnons une estimation précise de la vitesse de convergence de la solution vers un profil donné quand le temps tend vers l'infini. Ce résultat est obtenu à l'aide de divers outils tels que des techniques de symétrisation et des inégalités fonctionnelles optimales. Les derniers chapitres traitent de résultats numériques et de calculs formels liés au modèle Keller-Segel / In this thesis we study the set of solutions of partial differential equations arising from models in astrophysics and biology. We answer the questions of existence but also we try to describe the behavior of some families of solutions when parameters vary. First we study two problems concerned with astrophysics, where we show the existence of particular sets of solutions depending on a parameter using the Lyapunov-Schmidt reduction method. Afterwards a perturbation argument and Banach's Fixed Point Theorem reduce the original problem to a finite-dimensional one, which can be solved, usually, by variational techniques. The rest of the thesis is de-voted to the study of the Keller-Segel model, which describes the motion of unicellular amoebae. In its simpler version, the Keller-Segel model is a parabolic-elliptic system which shares with some gravitational models the property that interaction is computed through an attractive Poisson / Newton equation. A major difference is the fact that it is set in a two-dimensional setting, which experimentally makes sense, while gravitational models are ordinarily three-dimensional. For this problem the existence issues are well known, but the behaviour of the solutions during the time evolution is still an active area of research. Here we extend properties already known in particular regimes to a broader range of the mass parameter, and we give a precise estimate of the convergence rate of the solution to a known profile as time goes to infinity. This result is achieved using various tools such as symmetrization techniques and optimal functional inequalities. The last chapters deal with numerical results and formal computations related to the Keller-Segel model