Almost sure estimates for the concentration neighborhood of Sinai's walk

We consider Sinai's random walk in random environment. We prove that infinitely often (i.o.) the size of the concentration neighborhood of this random walk is almost surely bounded. As an application we get that i.o. the maximal distance between two favorite sites is almost surely bounded

The local time of a random walk on growing hypercubes

We study a random walk in a random environment (RWRE) on $\Z^d$, $1 \leq d < +\infty$. The main assumptions are that conditionned on the environment the random walk is reversible. Moreover we construct our environment in such a way that the walk can't be trapped on a single point like in some particular RWRE but in some specific d-1 surfaces. These surfaces are basic surfaces with deterministic geometry. We prove that the local time in the neighborhood of these surfaces is driven by a function of the (random) reversible measure. As an application we get the limit law of the local time as a process on these surfaces.Comment: 24 page

Limit law of the local time for Brox's diffusion

We consider Brox's model: a one-dimensional diffusion in a Brownian potential W. We show that the normalized local time process (L(t;m_(log t) + x)=t; x \in R), where m_(log t) is the bottom of the deepest valley reached by the process before time t, behaves asymptotically like a process which only depends on W. As a consequence, we get the weak convergence of the local time to a functional of two independent three-dimensional Bessel processes and thus the limit law of the supremum of the normalized local time. These results are discussed and compared to the discrete time and space case which same questions have been solved recently by N. Gantert, Y. Peres and Z. Shi

On the concentration of Sinai's walk

We consider Sinai's random walk in random environment. We prove that for an interval of time [1,n] Sinai's walk sojourns in a small neighborhood of the point of localization for the quasi totality of this amount of time. Moreover the local time at the point of localization normalized by $n$ converges in probability to a well defined random variable of the environment

Renewal structure and local time for diffusions in random environment

We study a one-dimensional diffusion $X$ in a drifted Brownian potential $W\_\kappa$, with 0\textless{}\kappa\textless{}1, and focus on the behavior of the local times $(\mathcal{L}(t,x),x)$ of $X$ before time t\textgreater{}0.In particular we characterize the limit law of the supremum of the local time, as well as the position of the favorite sites. These limits can be written explicitly from a two dimensional stable L{\'e}vy process. Our analysis is based on the study of an extension of the renewal structure which is deeply involved in the asymptotic behavior of $X$.Comment: 61 page

A limit result for a system of particles in random environment

We consider an infinite system of particles in one dimension, each particle performs independant Sinai's random walk in random environment. Considering an instant $t$, large enough, we prove a result in probability showing that the particles are trapped in the neighborhood of well defined points of the lattice depending on the random environment the time $t$ and the starting point of the particles.Comment: 11 page

Localisation et Concentration de la Marche de Sinai

Jury : M. Enrique ANDJEL, M. François BENTOSELA, M. Francis COMETS, M. Pierre PICCO, M. Zhan SHISinai's walk is an elementary model of one dimensional random walk in random environment doing nearest neighbourhood jump. We impose three conditions on the random environment: two necessaries hypothesis to get a recurrent process but not a simple random walk and a hypothesis of regularity which allows us to have a good control on the fluctuations of the random environment. The asymptotic behaviour of such a walk was discovered by Y. Sinai in 1982: he shows that this process is sub-diffusive and that at time n it is located in the neighbourhood of a well defined point of the lattice. This point is a random variable depending only on the random environment and n, his explicit limit distribution was given by H. Kesten and A. O. Golosov (independently) in 1986. A part of this work (part II) gives an alternative proof of Sinai's results. The detailed study of the results of localization has motivated the study of a new aspect of the behaviour of Sinai' walk, we called it concentration phenomena (part III of the present thesis). We prove that it is concentrated in a small neighbourhood of the point of localization; this means that for an interval of time n Sinai's walk spends the quasi totality of this amount of time n in the neighbourhood of the point of localization. The size of this neighbourhood is negligible comparing to the typical range of Sinai's walk. The other result we show is that the local time of this random walk on the point of localization normalized by n converges in probability to a random variable depending only on n and on the random environment. This random variable is the inverse of the mean of the local time in the valley where the walk is prisoner, in a return time to the point of localization. All our results are “quenched” results, this mean that we work with a fixed environment that belongs to a probability subset of the random media and it is shown that this probability subset has a probability that goes to one. From these results we give some consequences on the maximum of the local time and the favourite site of Sinai's walk, in particular we show that all the favourite site and Sinai's walk, properly normalized, have the same limiting distribution.La marche de Sinai est un modèle élémentaire de marches aléatoires en milieu aléatoire unidimensionnelle effectuant des sauts unités sur ses plus proches voisins. On impose trois conditions sur le milieu aléatoire : deux hypothèses nécessaires pour obtenir un processus récurrent non réduit à un marche aléatoire simple et une hypothèse de régularité qui nous permet un bon contrôle des fluctuations du milieu aléatoire. Le comportement asymptotique de ce processus a été découvert par Y. Sinai en 1982 : il montre qu'il est sous diffusif et que pour instant n donné il est localisé dans le voisinage d'un point déterminé du réseau. Ce point est une variable aléatoire dépendant uniquement du milieu aléatoire et de n dont la distribution limite a été déterminée par H. Kesten et A. O. Golosov (indépendamment) en 1986. Une partie de cette thèse (partie II) a eu pour but de donner une preuve alternative au résultat de Y. Sinai . L'étude détaillée des résultats sur la localisation nous a permis de découvrir un nouvel aspect du comportement de la marche de Sinai que nous avons appelé concentration (partie III de la thèse). Nous avons montré que celle-ci était concentrée dans un voisinage restreint du point de localisation, c'est-à-dire que pour un intervalle de temps de longueur n la marche de Sinai passe la quasi-totalité de ce temps n dans un voisinage du point de localisation dont la taille est négligeable devant la distance parcourue. Nous avons également montré que le temps local de la marche de Sinai au point de localisation normalisé par n converge en probabilité vers une variable aléatoire dépendant uniquement du milieu et de n. Cette variable aléatoire est l'inverse de la moyenne du temps local dans la vallée où la marche de Sinai reste prisonnière, en un temps de retour au point de localisation. Les résultats que nous avons obtenus sont de type « trempé », c'est-à-dire que l'on travaille avec un milieu aléatoire appartenant à un sous-espace de probabilité du milieu aléatoire et on montre que ce sous-espace à une probabilité qui tend vers 1. De ces résultats est apparu des conséquences naturelles sur le maximum des temps locaux et le lieu favori de la marche de Sinai, notamment nous avons montré que la marche de Sinai et les lieux favoris de cette marche, correctement normalisés, ont même distribution limite