Les modèles de tenseurs sont des mesures de probabilité sur des espaces de tenseurs aléatoires. Ils généralisent les modèles de matrices et furent développés pour l’étude de la géométrie aléatoire en dimension arbitraire. De plus, ils sont fortement liés aux théories de gravité quantique car, en plus des modèles standards très simples, ils incluent les théories de champs sur groupes, qui constituent l’approche « intégrale fonctionnelle » de la gravité quantique à boucle. Dans cette thèse, nous étudions le cas restreint des modèles tensoriels quartiques, pour lesquels un plus grand nombre de résultats mathématiques rigoureux ont pu être démontrés. Grâce à la transformation de champ intermédiaire, les modèles quartiques peuvent être ré-écrits sous forme de modèles de matrices multiples, et leurs développements perturbatifs peuvent être indexés par des cartes combinatoires. En utilisant divers développement en cartes, nous démontrons d’importants résultats d’analycité ainsi que des bornes pour les cumulants du modèle tensoriel standard le plus général et de rang arbitraire, ainsi que du plus simple modèle renormalisable de rang 3. Ensuite, nous introduisons une nouvelle famille de modèles, les modèles améliorés, dont le développement perturbatif se comporte de manière nouvelle, différente du comportement « melonique » qui caractérise les modèles tensoriels précédemment étudiés. / Tensor models are probability measures for random tensors. They generalise matrix models and were developed to study random geometry in arbitrary dimension. Moreover, they are strongly connected to quantum gravity theories as, additionally to the standard bare-bones models, they encompass the field theoretical approach to loop quantum gravity known as group field theory.In the present thesis, we focus on the restricted case of quartic tensor models, for which a far greater number of rigorous mathematical results have been proven. Quartic models can be re-written as multi-matrix models using the intermediate field representation, and their perturbative expansions can be written as series expansions over combinatorial maps. Using a variety of map expansions, we prove analyticity results and useful bounds for the cumulants of various tensor models : the most general standard quartic model at any rank and the simplest renormalisable tensor field theory at rank 3. Then, we introduce a new class of models, the enhanced models, which perturbative expansions display new behaviour, different to the so called melonic behaviour that characterise most known tensor models so far.

This thesis focusses on the properties of, and relationships between, several fundamental objects arising from critical physical models. In particular, we consider Schramm--Loewner evolutions, the Gaussian free field, Liouville quantum gravity and the Brownian continuum random tree. We begin by considering branching diffusions in a bounded domain $D\subset$ $R^{d}$, in which particles are killed upon hitting the boundary $\partial D$. It is known that such a system displays a phase transition in the branching rate: if it exceeds a critical value, the population will no longer become extinct almost surely. We prove that at criticality, under mild assumptions on the branching mechanism and diffusion, the genealogical tree associated with the process will converge to the Brownian CRT. Next, we move on to study Gaussian multiplicative chaos. This is the rigorous framework that allows one to make sense of random measures built from rough Gaussian fields, and again there is a parameter associated with the model in which a phase transition occurs. We prove a uniqueness and convergence result for approximations to these measures at criticality. From this point onwards we restrict our attention to two-dimensional models. First, we give an alternative, ``non-Gaussian" construction of Liouville quantum gravity (a special case of Gaussian multiplicative chaos associated with the 2-dimensional Gaussian free field), that is motivated by the theory of multiplicative cascades. We prove that the Liouville (GMC) measures associated with the Gaussian free field can be approximated using certain sequences of ``local sets" of the field. This is a particularly natural construction as it is both local and conformally invariant. It includes the case of nested CLE$_{4}$, when it is coupled with the GFF as its set of ``level lines". Finally, we consider this level line coupling more closely, now when it is between SLE$_{4}$ and the GFF. We prove that level lines can be defined for the GFF with a wide range of boundary conditions, and are given by SLE$_{4}$-type curves. As a consequence, we extend the definition of SLE$_{4}(\rho)$ to the case of a continuum of force points.

Dans ce travail de thèse, nous étudions les fluctuations macroscopiques dans un modèle de boules aléatoires. Un modèle de boules aléatoires est une agrégation de boules dans Rd dont les centres et les rayons sont aléatoires. On marque également chaque boule par un poids aléatoire. On considère la masse M induite par le système de boules pondérées sur une configuration μ de Rd. Pour réaliser l’étude macroscopique des fluctuations de M, on réalise un "dézoom" sur la configuration de boules. Mathématiquement cela revient à diminuer le rayon moyen tout en augmentant le nombre moyen de centres par unité de volume. La question a déjà été étudiée lorsque les composantes des triplets (centre, rayon, poids) sont indépen- dantes et que ces triplets sont engendrés selon un processus ponctuel de Poisson sur Rd × R+ × R. On observe alors trois comportements distincts selon le rapport de force entre la vitesse de diminution des rayons et la vitesse d’augmentation de la densité des boules. Nous proposons de généraliser ces résultats dans trois directions distinctes. La première partie de ce travail de thèse consiste à introduire de la dépendance entre les centres et les rayons et de l’inhomogénéité dans la répartition des centres. Dans le modèle que nous proposons, le comportement stochastique des rayons dépend de l’emplacement de la boule. Dans les travaux précédents, les convergences obtenues pour les fluctuations de M sont au mieux des convergences fonctionnelles en dimension finie. Nous obtenons, dans la deuxième partie de ce travail, de la convergence fonctionnelle sur un ensemble de configurations μ de dimension infinie. Dans une troisième et dernière partie, nous étudions un modèle de boules aléatoires (non pondérées) sur C dont les couples (centre, rayon) sont engendrés par un processus ponctuel déterminantal. Contrairement au processus ponctuel de Poisson, le processus ponctuel déterminantal présente des phénomènes de répulsion entre ses points ce qui permet de modéliser davantage de problèmes physiques. / In this thesis, we study the macroscopic fluctuations in random balls models. A random balls model is an aggregation of balls in Rd whose centers and radii are random. We also mark each balls with a random weight. We consider the mass M induced by the system of weighted balls on a configuration μ of Rd. In order to investigate the macroscopic fluctuations of M, we realize a zoom-out on the configuration of balls. Mathematically, we reduce the mean radius while increasing the mean number of centers by volume unit. The question has already been studied when the centers, the radii and the weights are independent and the triplets (center, radius, weight) are generated according to a Poisson point process on Rd ×R+ ×R. Then, we observe three different behaviors depending on the comparison between the speed of the decreasing of the radii and the speed of the increasing of the density of centers. We propose to generalize these results in three different directions. The first part of this thesis consists in introducing dependence between the radii and the centers and inhomogeneity in the distribution of the centers. In the model we propose, the stochastic behavior of the radii depends on the location of the ball. In the previous works, the convergences obtained for the fluctuations of M are at best functional convergences in finite dimension. In the second part of this work, we obtain functional convergence on an infinite dimensional set of configurations μ. In the third and last part, we study a random balls model (non-weighted) on C where the couples (center, radius) are generated according to determinantal point process. Unlike to the Poisson point process, the determinantal point process exhibits repulsion phenomena between its points which allows us to model more physical problems.

Cette thèse présente un certain nombre d'outils permettant d'approfondir notre compréhension de la physique sous-jacente de théories des champs appelées GFTs (Group Field Theories). Ces théories trouvent leur origines dans différentes voies de recherches en gravité quantique, en particulier les mousses de spin et les tenseurs aléatoires, et on une interprétation de modèles d'espace-temps quantique, ou "pré-géométrique", les amplitudes de Feynman étant indexées par des triangulations. La compréhension du passage entre cette vision "discrète" et notre espace-temps continue reste le grand défi de ces théories, défi pour lequel la renormalisation, la construction de théories effectives, la recherche de point fixes et de transitions de phases s'avère primordiale, et c'est dans le but de comprendre les outils nécessaires à cette description que cette thèse a vu le jour. Nous nous attacherons dans un premier temps à donner une description concise de la renormalisation perturbative, et à l'établissement d'un système d'équations fermées décrivant exactement l'ordre dominant de la théorie. Dans un second temps, nous détaillerons la mise en application de méthodes non-perturbative. Le groupe de renormalisation fonctionnel en premier lieu, permettra de donner une première description non-perturbative de ces théories, et de voir apparaître certain points fixes non-triviaux. Une approche constructive enfin, discutée sur deux modèles, ouvre la voie vers un programme visant à donner une définition rigoureuse de ces théories dans un régime non-perturbatif. / This thesis presents a number of tools to deepen our understanding of the underlying physics theories called fields GFTs (Group Field Theories). These theories found their origins in different approaches of quantum gravity, in particular spin foams and random tensors, and are interpreted as quantum space-time or "pre-geometric" models, the amplitudes of Feynman being indexed by triangulations. The understanding of the passage between this "discrete" vision to our continuous space-time remains the great challenge of these theories, for which renormalization, effective theories, research of fixed points and phase transitions proves paramount, and it is the aim of this thesis to understand the tools required for this description. In a first time, we will focus to give a concise description of the perturbative renormalization, and the establishment of a closed system of equations describing exactly the leading order of the theory. Secondly, we will detail the implementation of nonperturbative methods. The functional renormalization group in the first place, providing a first non-perturbative description of these theories, and some nontrivial fixed points. Finally, a constructive approach discussed on two models open the way to a rigorous definition of these theories beyond the perturbative level.

Estimativa e simulação baseados na estatística de dois pontos têm sido usadas desde a década de 1960 na análise geoestatístico. Esses métodos dependem do modelo de correlação espacial derivado da bem conhecida função semivariograma. Entretanto, a função semivariograma não pode descrever a heterogeneidade geológica encontrada em depósitos minerais e reservatórios de petróleo. Assim, ao invés de usar a estatística de dois pontos, a geoestatística multi-pontos, baseada em distribuições de probabilidade de múltiplo pontos, tem sido considerada uma alternativa confiável para descrição da heterogeneidade geológica. Nessa tese, o algoritmo multi-ponto é revisado e uma nova solução é proposta. Essa solução é muito melhor que a original, pois evita usar as probabilidades marginais quando um evento que nunca ocorre é encontrado no template. Além disso, para cada realização a zona de incerteza é ressaltada. Uma base de dados sintética foi gerada e usada como imagem de treinamento. A partir dessa base de dados completa, uma amostra com 25 pontos foi extraída. Os resultados mostram que a aproximação proposta proporciona realizações mais confiáveis com zonas de incerteza menores. / Estimation and simulation based on two-point statistics have been used since 1960\'s in geostatistical analysis. These methods depend on the spatial correlation model derived from the well known semivariogram function. However, the semivariogram function cannot describe the geological heterogeneity found in mineral deposits and oil reservoirs. Thus, instead of using two-point statistics, multiple-point geostatistics based on probability distributions of multiple-points has been considered as a reliable alternative for describing the geological heterogeneity. In this thesis, the multiple-point algorithm is revisited and a new solution is proposed. This solution is much better than the former one because it avoids using marginal probabilities when a never occurring event is found in a template. Moreover, for each realization the uncertainty zone is highlighted. A synthetic data base was generated and used as training image. From this exhaustive data set, a sample with 25 points was drawn. Results show that the proposed approach provides more reliable realizations with smaller uncertainty zones.

Estimativa e simulação baseados na estatística de dois pontos têm sido usadas desde a década de 1960 na análise geoestatístico. Esses métodos dependem do modelo de correlação espacial derivado da bem conhecida função semivariograma. Entretanto, a função semivariograma não pode descrever a heterogeneidade geológica encontrada em depósitos minerais e reservatórios de petróleo. Assim, ao invés de usar a estatística de dois pontos, a geoestatística multi-pontos, baseada em distribuições de probabilidade de múltiplo pontos, tem sido considerada uma alternativa confiável para descrição da heterogeneidade geológica. Nessa tese, o algoritmo multi-ponto é revisado e uma nova solução é proposta. Essa solução é muito melhor que a original, pois evita usar as probabilidades marginais quando um evento que nunca ocorre é encontrado no template. Além disso, para cada realização a zona de incerteza é ressaltada. Uma base de dados sintética foi gerada e usada como imagem de treinamento. A partir dessa base de dados completa, uma amostra com 25 pontos foi extraída. Os resultados mostram que a aproximação proposta proporciona realizações mais confiáveis com zonas de incerteza menores. / Estimation and simulation based on two-point statistics have been used since 1960\'s in geostatistical analysis. These methods depend on the spatial correlation model derived from the well known semivariogram function. However, the semivariogram function cannot describe the geological heterogeneity found in mineral deposits and oil reservoirs. Thus, instead of using two-point statistics, multiple-point geostatistics based on probability distributions of multiple-points has been considered as a reliable alternative for describing the geological heterogeneity. In this thesis, the multiple-point algorithm is revisited and a new solution is proposed. This solution is much better than the former one because it avoids using marginal probabilities when a never occurring event is found in a template. Moreover, for each realization the uncertainty zone is highlighted. A synthetic data base was generated and used as training image. From this exhaustive data set, a sample with 25 points was drawn. Results show that the proposed approach provides more reliable realizations with smaller uncertainty zones.