L'objet de cette thèse est d'étudier une certaine classe de processus de Markov, dits déterministes par morceaux, ayant de très nombreuses applications en modélisation. Plus précisément, nous nous intéresserons à leur comportement en temps long et à leur vitesse de convergence à l'équilibre lorsqu'ils admettent une mesure de probabilité stationnaire. L'un des axes principaux de ce manuscrit de thèse est l'obtention de bornes quantitatives fines sur cette vitesse, obtenues principalement à l'aide de méthodes de couplage. Le lien sera régulièrement fait avec d'autres domaines des mathématiques dans lesquels l'étude de ces processus est utile, comme les équations aux dérivées partielles. Le dernier chapitre de cette thèse est consacré à l'introduction d'une approche unifiée fournissant des théorèmes limites fonctionnels pour étudier le comportement en temps long de chaînes de Markov inhomogènes, à l'aide de la notion de pseudo-trajectoire asymptotique. / The purpose of this Ph.D. thesis is the study of piecewise deterministic Markov processes, which are often used for modeling many natural phenomena. Precisely, we shall focus on their long time behavior as well as their speed of convergence to equilibrium, whenever they possess a stationary probability measure. Providing sharp quantitative bounds for this speed of convergence is one of the main orientations of this manuscript, which will usually be done through coupling methods. We shall emphasize the link between Markov processes and mathematical fields of research where they may be of interest, such as partial differential equations. The last chapter of this thesis is devoted to the introduction of a unified approach to study the long time behavior of inhomogeneous Markov chains, which can provide functional limit theorems with the help of asymptotic pseudotrajectories.

This work motivates the study of open dynamical systems corresponding to the doubling map. In particular, the dynamical properties of the attractor of the doubling map when a symmetric, centred open interval is removed are studied. Using the arithmetical properties of the binary expansion of the points on the boundary of the removed interval, we study properties such as topological transitivity, the specification property and intrinsic ergodicity. The properties of the function that associates to each hole $(a,b)$ the topological entropy of the attractor of the considered dynamical system are also shown. For these purposes, a subshift corresponding to an element of the lexicographic world is associated to each attractor and the mentioned properties are studied symbolically.

Cette thèse est constituée de deux parties indépendantes. La première partie concerne l'étude des vecteurs propres de matrices aléatoires de type Wigner. Dans un premier temps, nous étudions la distribution des vecteurs propres de matrices de Wigner déformées, elles consistent en une perturbation d'une matrice de Wigner par une matrice diagonale déterministe. Si les deux matrices sont du même ordre de grandeur, il a été prouvé que les vecteurs propres se délocalisent complètement et les valeurs propres rentrent dans la classe d'universalité de Wigner-Dyson-Mehta. Nous étudions ici une phase intermédiaire où la perturbation déterministe domine l'aléa: les vecteurs propres ne sont pas totalement délocalisés alors que les valeurs propres restent universelles. Les entrées des vecteurs propres sont asymptotiquement gaussiennes avec une variance qui les localise dans une partie explicite du spectre. De plus, leur masse est concentrée autour de cette variance dans le sens d'une unique ergodicité quantique. Ensuite, nous étudions des corrélations de différents vecteur propres. Pour se faire, une nouvelle observable sur les moments de vecteurs propres du mouvement brownien de Dyson est étudiée. Elle suit une équation parabolique close qui est un pendant fermionique du flot des moments de vecteurs propres de Bourgade-Yau. En combinant l'étude de ces deux observables, il est possible d'analyser certaines corrélations.La deuxième partie concerne l'étude de la distribution des valeurs propres de modèles non-linéaires de matrices aléatoires. Ces modèles apparaissent dans l'étude de réseaux de neurones aléatoires et correspondent à une version non-linéaire de matrice de covariance dans le sens où une fonction non-linéaire, appelée fonction d'activation, est appliquée entrée par entrée sur la matrice. La distribution des valeurs propres convergent vers une distribution déterministe caractérisée par une équation auto-consistante de degré 4 sur sa transformée de Stieltjes. La distribution ne dépend de la fonction que sur deux paramètres explicites et pour certains choix de paramètres nous retrouvons la distribution de Marchenko-Pastur qui reste stable après passage sous plusieurs couches du réseau de neurones. / This thesis consists in two independent parts. The first part pertains to the study of eigenvectors of random matrices of Wigner-type. Firstly, we analyze the distribution of eigenvectors of deformed Wigner matrices which consist in a perturbation of a Wigner matrix by a deterministic diagonal matrix. If the two matrices are of the same order of magnitude, it was proved that eigenvectors are completely delocalized and eigenvalues belongs to the Wigner-Dyson-Mehta universality class. We study here an intermediary phase where the deterministic perturbation dominates the randomness of the Wigner matrix : eigenvectors are not completely delocalized but eigenvalues are still universal. The eigenvector entries are asymptotically Gaussian with a variance which localize them onto an explicit part of the spectrum. Moreover, their mass is concentrated around their variance in a sense of a quantum unique ergodicity property. Then, we consider correlations of different eigenvectors. To do so, we exhibit a new observable on eigenvector moments of the Dyson Brownian motion. It follows a closed parabolic equation which is a fermionic counterpart of the Bourgade-Yau eigenvector moment flow. By combining the study of these two observables, it becomes possible to study some eigenvector correlations.The second part concerns the study of eigenvalue distribution of nonlinear models of random matrices. These models appear in the study of random neural networks and correspond to a nonlinear version of sample covariance matrices in the sense that a nonlinear function, called the activation function, is applied entrywise to the matrix. The empirical eigenvalue distribution converges to a deterministic distribution characterized by a self-consistent equation of degree 4 followed by its Stieltjes transform. The distribution depends on the function only through two explicit parameters. For a specific choice of these parameters, we recover the Marchenko-Pastur distribution which stays stable after going through several layers of the network.

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A dynamical system originally invented by Boltzmann has had recent developments. The system consists of a particle in a gravitational potential with an added centrifugal force, which is subject to reflection against a wall that separates the system from the gravitational center. The recent developments are with regards to the integrability of the system in the special case of vanishing centrifugal term. The purpose of this essay is to explicate these developments. / Ett dynamiskt system, ursprungligen uppfunnet av Boltzmann, har nyligen sett utvecklingar. Systemet består av en partikel i en gravitationspotential med en tillagd centrifugalkraft, som reflekterar vid kontakt med en vägg som skiljer partikeln och gravitationscentrumet. De nya utvecklingarna är inom systemets integrabilitet i det specialfall att centrifugalkraften är borttagen. Syftet med denna uppsats är att explicera dessa framtaganden.

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Generalized hill climbing (GHC) algorithms provide a framework for using local search algorithms to address intractable discrete optimization problems. Many well-known local search algorithms can be formulated as GHC algorithms, including simulated annealing, threshold accepting, Monte Carlo search, and pure local search (among others). This dissertation develops a mathematical framework for simultaneously addressing a set of related discrete optimization problems using GHC algorithms. The resulting algorithms, termed simultaneous generalized hill climbing (SGHC) algorithms, can be applied to a wide variety of sets of related discrete optimization problems. The SGHC algorithm probabilistically moves between these discrete optimization problems according to a problem generation probability function. This dissertation establishes that the problem generation probability function is a stochastic process that satisfies the Markov property. Therefore, given a SGHC algorithm, movement between these discrete optimization problems can be modeled as a Markov chain. Sufficient conditions that guarantee that this Markov chain has a uniform stationary probability distribution are presented. Moreover, sufficient conditions are obtained that guarantee that a SGHC algorithm will visit the globally optimal solution over all the problems in a set of related discrete optimization problems. Computational results are presented with SGHC algorithms for a set of traveling salesman problems. For comparison purposes, GHC algorithms are also applied individually to each traveling salesman problem. These computational results suggest that optimal/near optimal solutions can often be reached more quickly using a SGHC algorithm. / Ph. D.

For a general attractive Probabilistic Cellular Automata on S-Zd, we prove that the (time-) convergence towards equilibrium of this Markovian parallel dynamics, exponentially fast in the uniform norm, is equivalent to a condition (A). This condition means the exponential decay of the influence from the boundary for the invariant measures of the system restricted to finite boxes. For a class of reversible PCA dynamics on {1,+1}(Zd), wit a naturally associated Gibbsian potential rho, we prove that a (spatial-) weak mixing condition (WM) for rho implies the validity of the assumption (A); thus exponential (time-) ergodicity of these dynamics towards the unique Gibbs measure associated to rho hods. On some particular examples we state that exponential ergodicity holds as soon as there is no phase transition.