Dirichlet random walks

This article provides tools for the study of the Dirichlet random walk in $\mathbb{R}^d$. By this we mean the random variable $W=X_1\Theta_1+\cdots+X_n\Theta_n$ where $X=(X_1,\ldots,X_n) \sim \mathcal{D}(q_1,\ldots,q_n)$ is Dirichlet distributed and where $\Theta_1,\ldots \Theta_n$ are iid, uniformly distributed on the unit sphere of $\mathbb{R}^d$ and independent of $X.$ In particular we compute explicitely in a number of cases the distribution of $W.$ Some of our results appear already in the literature, in particular in the papers by G\'erard Le Ca\"{e}r (2010, 2011). In these cases, our proofs are much simpler from the original ones, since we use a kind of Stieltjes transform of $W$ instead of the Laplace transform: as a consequence the hypergeometric functions replace the Bessel functions. A crucial ingredient is a particular case of the classical and non trivial identity, true for $0\leq u\leq 1/2$:$$_2F_1(2a,2b;a+b+\frac{1}{2};u)= \_2F_1(a,b;a+b+\frac{1}{2};4u-4u^2).$$ We extend these results to a study of the limits of the Dirichlet random walks when the number of added terms goes to infinity, interpreting the results in terms of an integral by a Dirichlet process. We introduce the ideas of Dirichlet semigroups and of Dirichlet infinite divisibility and characterize these infinite divisible distributions in the sense of Dirichlet when they are concentrated on the unit ball of $\mathbb{R}^d.$ {4mm}\noindent \textsc{Keywords:} Dirichlet processes, Stieltjes transforms, random flight, distributions in a ball, hyperuniformity, infinite divisibility in the sense of Dirichlet. {4mm}\noindent \textsc{AMS classification}: 60D99, 60F99

Random walks in random Dirichlet environment are transient in dimension d≥3d\ge 3

We consider random walks in random Dirichlet environment (RWDE) which is a special type of random walks in random environment where the exit probabilities at each site are i.i.d. Dirichlet random variables. On $\Z^d$, RWDE are parameterized by a $2d$-uplet of positive reals. We prove that for all values of the parameters, RWDE are transient in dimension $d\ge 3$. We also prove that the Green function has some finite moments and we characterize the finite moments. Our result is more general and applies for example to finitely generated symmetric transient Cayley graphs. In terms of reinforced random walks it implies that directed edge reinforced random walks are transient for $d\ge 3$.Comment: New version published at PTRF with an analytic proof of lemma

Random Dirichlet environment viewed from the particle in dimension d≥3d\ge 3

We consider random walks in random Dirichlet environment (RWDE) which is a special type of random walks in random environment where the exit probabilities at each site are i.i.d. Dirichlet random variables. On ${\mathbb Z}^d$, RWDE are parameterized by a 2d-uplet of positive reals called weights. In this paper, we characterize for $d\ge 3$ the weights for which there exists an absolutely continuous invariant probability for the process viewed from the particle. We can deduce from this result and from [27] a complete description of the ballistic regime for $d\ge 3$.Comment: 18 pages. arXiv admin note: text overlap with arXiv:1205.5709 by other authors without attributio

A family of random walks with generalized Dirichlet steps

We analyze a class of continuous time random walks in $\mathbb R^d,d\geq 2,$ with uniformly distributed directions. The steps performed by these processes are distributed according to a generalized Dirichlet law. Given the number of changes of orientation, we provide the analytic form of the probability density function of the position $\{\underline{\bf X}_d(t),t>0\}$ reached, at time $t>0$, by the random motion. In particular, we analyze the case of random walks with two steps. In general, it is an hard task to obtain the explicit probability distributions for the process $\{\underline{\bf X}_d(t),t>0\}$ . Nevertheless, for suitable values for the basic parameters of the generalized Dirichlet probability distribution, we are able to derive the explicit conditional density functions of $\{\underline{\bf X}_d(t),t>0\}$. Furthermore, in some cases, by exploiting the fractional Poisson process, the unconditional probability distributions are obtained. This paper extends in a more general setting, the random walks with Dirichlet displacements introduced in some previous papers

Random walks in a Dirichlet environment

This paper states a law of large numbers for a random walk in a random iid environment on ${\mathbb Z}^d$, where the environment follows some Dirichlet distribution. Moreover, we give explicit bounds for the asymptotic velocity of the process and also an asymptotic expansion of this velocity at low disorder.Comment: Change in theorem

A zero-one law for random walks in random environments on Z2\mathbb{Z}^2 with bounded jumps

This paper has two main results, which are connected through the fact that the first is a key ingredient in the second. Both are extensions of results concerning directional transience of nearest-neighbor random walks in random environments to allow for bounded jumps. Zerner and Merkl proved a 0-1 law for directional transience for planar random walks in random environments. We extend the result to non-planar i.i.d. random walks in random environments on $\mathbb{Z}^2$ with bounded jumps. Sabot and Tournier characterized directional transience for a given direction for nearest-neighbor random walks in Dirichlet environments on $\mathbb{Z}^d$, $d\geq1$. We extend this characterization to random walks in Dirichlet environments with bounded jumps.Comment: 27 pages, 6 figure

Random walks in Dirichlet environment: an overview

Random Walks in Dirichlet Environment (RWDE) correspond to Random Walks in Random Environment (RWRE) on $\Bbb{Z}^d$ where the transition probabilities are i.i.d. at each site with a Dirichlet distribution. Hence, the model is parametrized by a family of positive weights $(\alpha_i)_{i=1, \ldots, 2d}$, one for each direction of $\Bbb{Z}^d$. In this case, the annealed law is that of a reinforced random walk, with linear reinforcement on directed edges. RWDE have a remarkable property of statistical invariance by time reversal from which can be inferred several properties that are still inaccessible for general environments, such as the equivalence of static and dynamic points of view and a description of the directionally transient and ballistic regimes. In this paper we give a state of the art on this model and several sketches of proofs presenting the core of the arguments. We also present new computation of the large deviation rate function for one dimensional RWDE.Comment: 35 page