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.

Les résultats de cette thèse sont composés de trois parties relativement indépendantes.Dans la première partie, nous reprenons le problème de la définition d'une classe de processus markoviens à une infinité de coordonnées (systèmes de particules en interaction). Nous en proposons une construction ne mettant en jeu ni d'analyse fonctionnelle (ou peu), ni de problème de martingale. Ceci est fait en utilisant des outils probabilistes élémentaires, notamment des couplages adéquats. On fait pour cela une certaine hypothèse sur les taux individuels de transition, qui a été déjà exploitée dans la construction de T. M. Liggett (1972) notamment. Notre construction a l'avantage d'expliquer, plus concrètement que dans les autres constructions, le caractère naturel de cette hypothèse.Dans une seconde partie, nous considérons un modèle de croissance cristalline introduit par D. J. Gates et M. Westcott en 1987, où des particules du milieu environnant s'agrègent à la surface d'un cristal à maille carrée. Le modèle est caractérisé par des taux de déposition en chaque site qui prennent une certaine forme. Nos résultats portent principalement sur la question de la récurrence et de la récurrence positive de la surface du cristal en fonction de certains paramètres. Nous montrons notamment l'existence d'une zone de paramètres dans laquelle transience et récurrence positive coexistent, et suspectée de présenter un phénomène critique. / The results of this thesis are organized in three parts that are nearly independent.In the first part, we treat the problem of the defintion of a class of Markov processes with infinitely many coordinates, namely interacting particle systems. We propose a construction involving neither functional analysis, nor martingale problems. This is done using elementary probabilistic tools, such as proper couplings. Our technique requires a certain assumption on the jump rates which is, up to a slight generalization, the one used in T. M. Liggett's construction. Our construction has the advantage to give more intuition on the necessity of this assumption.In the second part, we consider a crystal growth model proposed by D. J. Gates and M. Westcott in 1987, where floating particles are packed on the surface of a square-lattice crystal, with prescribed deposition rates. We treat the question of the recurrence and positive recurrence of the interface, according to the value of certain parameters. We study especially a zone of parameters where transience and positive recurrence coexist. In this zone a critical phenomenon is suspected to occur.The third part deals with the question of the convergence in law for the subcritical contact process (on ZZ) seen from the edge, starting from a half-line of occupied sites. First we give an alternative proof of a recent result by E. D. Andjel, stating that convergence holds in a closely related discrete-time model. In continuous time we establish that the finite contact process seen from the edge has a Yaglom limit.

abstract: This dissertation investigates the dynamics of evolutionary games based on the framework of interacting particle systems in which individuals are discrete, space is explicit, and dynamics are stochastic. Its focus is on 2-strategy games played on a d-dimensional integer lattice with a range of interaction M. An overview of related past work is given along with a summary of the dynamics in the mean-field model, which is described by the replicator equation. Then the dynamics of the interacting particle system is considered, first when individuals are updated according to the best-response update process and then the death-birth update process. Several interesting results are derived, and the differences between the interacting particle system model and the replicator dynamics are emphasized. The terms selfish and altruistic are defined according to a certain ordering of payoff parameters. In these terms, the replicator dynamics are simple: coexistence occurs if both strategies are altruistic; the selfish strategy wins if one strategy is selfish and the other is altruistic; and there is bistability if both strategies are selfish. Under the best-response update process, it is shown that there is no bistability region. Instead, in the presence of at least one selfish strategy, the most selfish strategy wins, while there is still coexistence if both strategies are altruistic. Under the death-birth update process, it is shown that regardless of the range of interactions and the dimension, regions of coexistence and bistability are both reduced. Additionally, coexistence occurs in some parameter region for large enough interaction ranges. Finally, in contrast with the replicator equation and the best-response update process, cooperators can win in the prisoner's dilemma for the death-birth process in one-dimensional nearest-neighbor interactions. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2016

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This thesis is divided into two parts: In the first one (Chapters 1 and 2), we deal with problems arising from quantitative homogenization of the random elliptic operator in divergence form $-\\nabla \\cdot a \\nabla$. In Chapter 1 we study existence and stochastic bounds for the Green function $G$ associated to $-\\nabla \\cdot a \\nabla$ in the case of systems. Without assuming any regularity on the coefficient field $a= a(x)$, we prove that for every (measurable) uniformly elliptic tensor field $a$ and for almost every point $y \\in \\mathbb{R}^d$, there exists a unique Green\''s function centred in $y$ associated to the vectorial operator $-\\nabla \\cdot a\\nabla $ in $\\mathbb^d$, $d> 2$. In addition, we prove that if we introduce a shift-invariant ensemble $\\langle\\cdot \\rangle$ over the set of uniformly elliptic tensor fields, then $\\nabla G$ and its mixed derivatives $\\nabla \\nabla G$ satisfy optimal pointwise $L^1$-bounds in probability. Chapter 2 deals with the homogenization of $-\\nabla \\cdot a \\nabla$ to $-\\nabla \\ah \\nabla$ in the sense that we study the large-scale behaviour of $a$-harmonic functions in exterior domains $\\$ by comparing them with functions which are $\\ah$-harmonic. More precisely, we make use of the first and second-order correctors to compare an $a$-harmonic function $u$ to the two-scale expansion of suitable $\\ah$-harmonic function $u_h$. We show that there is a direct correspondence between the rate of the sublinear growth of the correctors and the smallness of the relative homogenization error $u- u_h$. The theory of stochastic homogenization of elliptic operators admits an equivalent probabilistic counterpart, which follows from the link between parabolic equations with elliptic operators in divergence form and random walks. This allows to reformulate the problem of homogenization in terms of invariance principle for random walks. The second part of thesis (Chapters 3 and 4) focusses on this interplay between probabilistic and analytic approaches and aims at exploiting it to study invariance principles in the case of degenerate random conductance models and systems of interacting particles. In Chapter 3 we study a random conductance model where we assume that the conductances are independent, stationary and bounded from above but not uniformly away from $0$. We give a simple necessary and sufficient condition for the relaxation of the environment seen by the particle to be diffusive in the sense of every polynomial moment. As a consequence, we derive polynomial moment estimates on the corrector which imply that the discrete elliptic operator homogenises or, equivalently, that the random conductance model satisfies a quenched invariance principle. In Chapter 4 we turn to a more complicated model, namely the symmetric exclusion process. We show a diffusive upper bound on the transition probability of a tagged particle in this process. The proof relies on optimal spectral gap estimates for the dynamics in finite volume, which are of independent interest. We also show off-diagonal estimates of Carne-Varopoulos type.

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Stochastic models describing how interacting individuals give rise to collective behaviour have become a widely used tool across disciplines—ranging from biology to physics to social sciences. Continuum population-level models based on partial differential equations for the population density can be a very useful tool (when, for large systems, particle-based models become computationally intractable), but the challenge is to predict the correct macroscopic description of the key attributes at the particle level (such as interactions between individuals and evolution rules). In this thesis we consider the simple class of models consisting of diffusive particles with short-range interactions. It is relevant to many applications, such as colloidal systems and granular gases, and also for more complex systems such as diffusion through ion channels, biological cell populations and animal swarms. To derive the macroscopic model of such systems, previous studies have used ad hoc closure approximations, often generating errors. Instead, we provide a new systematic method based on matched asymptotic expansions to establish the link between the individual- and the population-level models. We begin by deriving the population-level model of a system of identical Brownian hard spheres. The result is a nonlinear diffusion equation for the one-particle density function with excluded-volume effects enhancing the overall collective diffusion rate. We then expand this core problem in several directions. First, for a system with two types of particles (two species) we obtain a nonlinear cross-diffusion model. This model captures both alternative notions of diffusion, the collective diffusion and the self-diffusion, and can be used to study diffusion through obstacles. Second, we study the diffusion of finite-size particles through confined domains such as a narrow channel or a Hele–Shaw cell. In this case the macroscopic model depends on a confinement parameter and interpolates between severe confinement (e.g., a single- file diffusion in the narrow channel case) and an unconfined situation. Finally, the analysis for diffusive soft spheres, particles with soft-core repulsive potentials, yields an interaction-dependent non-linear term in the diffusion equation.

Nessa tese, estudamos o limite hidrodinâmico de um sistema estocástico de neurônios cujas interações são dadas por potenciais de Kac que imitam sinapses elétricas e químicas, e as correntes de vazamento. Esse sistema consiste de $\\ep^$ neurônios imersos em $[0,1)^2$, cada um disparando aleatoriamente de acordo com um processo pontual com taxa que depende tanto do seu potential de membrana como da posição. Quando o neurônio $i$ dispara, seu potential de membrana é resetado para $0$, enquanto que o potencial de membrana do neurônio $j$ é aumentado por um valor positivo $\\ep^2 a(i,j)$, se $i$ influencia $j$. Além disso, entre disparos consecutivos, o sistema segue uma movimento determinístico devido às sinapses elétricas e às correntes de vazamento. As sinapses elétricas estão envolvidas na sincronização do potencial de membrana dos neurônios, enquanto que as correntes de vazamento inibem a atividade de todos os neurônios, atraindo simultaneamente todos os potenciais de membrana para $0$. No principal resultado dessa tese, mostramos que a distribuição empírica dos potenciais de membrana converge, quando o parâmetro $\\ep$ tende à 0 , para uma densidade de probabilidade $ho_t(u,r)$ que satisfaz uma equação diferencial parcial nâo linear do tipo hiperbólica . / We study the hydrodynamic limit of a stochastic system of neurons whose interactions are given by Kac Potentials that mimic chemical and electrical synapses and leak currents. The system consists of $\\ep^$ neurons embedded in $[0,1)^2$, each spiking randomly according to a point process with rate depending on both its membrane potential and position. When neuron $i$ spikes, its membrane potential is reset to $0$ while the membrane potential of $j$ is increased by a positive value $\\ep^2 a(i,j)$, if $i$ influences $j$. Furthermore, between consecutive spikes, the system follows a deterministic motion due both to electrical synapses and leak currents. The electrical synapses are involved in the synchronization of the membrane potentials of the neurons, while the leak currents inhibit the activity of all neurons, attracting simultaneously their membrane potentials to 0. We show that the empirical distribution of the membrane potentials converges, as $\\ep$ vanishes, to a probability density $ho_t(u,r)$ which is proved to obey a nonlinear PDE of Hyperbolic type.

Le processus de contact est l'un des systèmes de particules en interaction les plus étudiés. Il peut s'interpréter comme un modèlepour la propagation d'un virus dans une population ou sur un réseau. L'objectif de cette thèse est d'étudier la relation entre la structure locale du réseau et le comportement global du processus sur le réseau tout entier.Le cadre typique dans lequel on se place est celui d’une suite de graphes aléatoires $(G_n)$ convergeant localement vers un graphe limite $G$.On étudie alors le comportement asymptotique du temps d’extinction $tau_n$ du processussur $G_n$; lorsqu’initialement tous les individus sont infectés. Nous montrons sur plusieurs exemples qu’il existe unetransition de phase lorsque $lambda$ - le taux d'infection du processus - traverse une valeur critique $ lambda_c (G)$, qui ne dépend que de $G$.Plus précisément, pour certains modèles de graphes aléatoires comme le modèle de configuration, le graphe d'attachement préférentiel, le graphe géométrique aléatoire, le graphe inhomogène, nous montrons que $ tau_n $ est d'ordre soit logarithmique soit exponentiel; selon que $ lambda$ est soit inférieur ou supérieur à $lambda_c (G) $.De plus, dans certains cas, nous montrons des résultats de métastablité: en régime sur-critique, $ tau_n $ divisé par son espérance converge en loi vers une variable aléatoire exponentielle de moyenne $1$, et la densité des sites infectés reste stable (et non nulle) sur une période de temps d’ordre typiquement $tau_n$. / The contact process is one of the most studied interacting particle systems and is also often interpreted as a model for the spread of a virus in a population or a network. The aim of this thesis is to study the relationship of the local structure of the network and the global behavior of the contact process (the virus) on the whole network. Let $(G_n)$ be a sequence of random graphs converging weakly to a graph $G$. Then we study $tau_n$, the extinction time of the contact process on $G_n$ starting from full occupancy. We prove in some examples that there is a phase transition of $tau_n$ when $lambda$ - the infection rate of the contact process crosses a critical value $lambda_c(G)$ depending only on $G$. More precisely, for some models of random graphs, such as the configuration model, preferential attachment graph, random geometric graph, inhomogeneous graph, we show that $tau_n$ is of logarithmic (resp. exponential) order when $lambda < lambda_c(G)$ (resp. $lambda < lambda_c(G)$). Moreover, in some cases we also prove metastable results: in the super-critical regime, $tau_n$ divided by its expectation converges in law to an exponential random variable with mean $1$, and the density of the infected sites is stable for a long time.

Nessa tese, estudamos o limite hidrodinâmico de um sistema estocástico de neurônios cujas interações são dadas por potenciais de Kac que imitam sinapses elétricas e químicas, e as correntes de vazamento. Esse sistema consiste de $\\ep^$ neurônios imersos em $[0,1)^2$, cada um disparando aleatoriamente de acordo com um processo pontual com taxa que depende tanto do seu potential de membrana como da posição. Quando o neurônio $i$ dispara, seu potential de membrana é resetado para $0$, enquanto que o potencial de membrana do neurônio $j$ é aumentado por um valor positivo $\\ep^2 a(i,j)$, se $i$ influencia $j$. Além disso, entre disparos consecutivos, o sistema segue uma movimento determinístico devido às sinapses elétricas e às correntes de vazamento. As sinapses elétricas estão envolvidas na sincronização do potencial de membrana dos neurônios, enquanto que as correntes de vazamento inibem a atividade de todos os neurônios, atraindo simultaneamente todos os potenciais de membrana para $0$. No principal resultado dessa tese, mostramos que a distribuição empírica dos potenciais de membrana converge, quando o parâmetro $\\ep$ tende à 0 , para uma densidade de probabilidade $ho_t(u,r)$ que satisfaz uma equação diferencial parcial nâo linear do tipo hiperbólica . / We study the hydrodynamic limit of a stochastic system of neurons whose interactions are given by Kac Potentials that mimic chemical and electrical synapses and leak currents. The system consists of $\\ep^$ neurons embedded in $[0,1)^2$, each spiking randomly according to a point process with rate depending on both its membrane potential and position. When neuron $i$ spikes, its membrane potential is reset to $0$ while the membrane potential of $j$ is increased by a positive value $\\ep^2 a(i,j)$, if $i$ influences $j$. Furthermore, between consecutive spikes, the system follows a deterministic motion due both to electrical synapses and leak currents. The electrical synapses are involved in the synchronization of the membrane potentials of the neurons, while the leak currents inhibit the activity of all neurons, attracting simultaneously their membrane potentials to 0. We show that the empirical distribution of the membrane potentials converges, as $\\ep$ vanishes, to a probability density $ho_t(u,r)$ which is proved to obey a nonlinear PDE of Hyperbolic type.