Showing papers in "Electronic Journal of Probability in 2004"

The Genealogy of Self-similar Fragmentations with Negative Index as a Continuum Random Tree

Abstract: We encode a certain class of stochastic fragmentation processes, namely self-similar fragmentation processes with a negative index of self-similarity, into a metric family tree which belongs to the family of Continuum Random Trees of Aldous. When the splitting times of the fragmentation are dense near 0, the tree can in turn be encoded into a continuous height function, just as the Brownian Continuum Random Tree is encoded in a normalized Brownian excursion. Under mild hypotheses, we then compute the Hausdorff dimensions of these trees, and the maximal Holder exponents of the height functions.

Differential Operators and Spectral Distributions of Invariant Ensembles from the Classical Orthogonal Polynomials. The Continuous Case

Abstract: Following the investigation by U. Haagerup and S. Thorbjornsen, we present a simple differential approach to the limit theorems for empirical spectral distributions of complex random matrices from the Gaussian, Laguerre and Jacobi Unitary Ensembles. In the framework of abstract Markov diffusion operators, we derive by the integration by parts formula differential equations for Laplace transforms and recurrence equations for moments of eigenfunction measures. In particular, a new description of the equilibrium measures as adapted mixtures of the universal arcsine law with an independent uniform distribution is emphasized. The moment recurrence relations are used to describe sharp, non asymptotic, small deviation inequalities on the largest eigenvalues at the rate given by the Tracy-Widom asymptotics.

Asymptotic Laws for Nonconservative Self-similar Fragmentations

Abstract: We consider a self-similar fragmentation process in which the generic particle of mass $x$ is replaced by the offspring particles at probability rate $x^\alpha$, with positive parameter $\alpha$. The total of offspring masses may be both larger or smaller than $x$ with positive probability. We show that under certain conditions the typical mass in the ensemble is of the order $t^{-1/\alpha}$ and that the empirical distribution of masses converges to a random limit which we characterise in terms of the reproduction law.

A General Analytical Result for Non-linear SPDE's and Applications

Abstract: Using analytical methods, we prove existence uniqueness and estimates for s.p.d.e. of the type $$ du_t+Au_tdt+f ( t,u_t ) dt+R g(t, u_t ) dt=h(t,x,u_t) dB_t, $$ where $A$ is a linear non-negative self-adjoint (unbounded) operator, $f$ is a nonlinear function which depends on $u$ and its derivatives controlled by $\sqrt{A}u$, $Rg$ corresponds to a nonlinearity involving $u$ and its derivatives of the same order as $Au$ but of smaller magnitude, and the right term contains a noise involving a $d$-dimensional Brownian motion multiplied by a non-linear function. We give a neat condition concerning the magnitude of these nonlinear perturbations. We also mention a few examples and, in the case of a diffusion generator, we give a double stochastic interpretation.

Chains with Complete Connections and One-Dimensional Gibbs Measures

Abstract: We discuss the relationship between one-dimensional Gibbs measures and discrete-time processes (chains). We consider finite-alphabet (finite-spin) systems, possibly with a grammar (exclusion rule). We establish conditions for a stochastic process to define a Gibbs measure and vice versa. Our conditions generalize well known equivalence results between ergodic Markov chains and fields, as well as the known Gibbsian character of processes with exponential continuity rate. Our arguments are purely probabilistic; they are based on the study of regular systems of conditional probabilities (specifications). Furthermore, we discuss the equivalence of uniqueness criteria for chains and fields and we establish bounds for the continuity rates of the respective systems of finite-volume conditional probabilities. As an auxiliary result we prove a (re)construction theorem for specifications starting from single-site conditioning, which applies in a more general setting (general spin space, specifications not necessarily Gibbsian).

Exchangeable Fragmentation-Coalescence Processes and their Equilibrium Measures

Abstract: We define and study a family of Markov processes with state space the compact set of all partitions of $N$ that we call exchangeable fragmentation-coalescence processes. They can be viewed as a combination of homogeneous fragmentation as defined by Bertoin and of homogenous coalescence as defined by Pitman and Schweinsberg or Mohle and Sagitov. We show that they admit a unique invariant probability measure and we study some properties of their paths and of their equilibrium measure.

Gaussian Scaling for the Critical Spread-out Contact Process above the Upper Critical Dimension

Abstract: We consider the critical spread-out contact process in $Z^d$ with $d\geq1$, whose infection range is denoted by $L\geq1$. The two-point function $\tau_t(x)$ is the probability that $x\in Z^d$ is infected at time $t$ by the infected individual located at the origin $o\in Z^d$ at time 0. We prove Gaussian behaviour for the two-point function with $L\geq L_0$ for some finite $L_0=L_0(d)$ for $d>4$. When $d\leq4$, we also perform a local mean-field limit to obtain Gaussian behaviour for $\tau_{ tT}(x)$ with $t>0$ fixed and $T\to\infty$ when the infection range depends on $T$ in such a way that $L_{T}=LT^b$ for any $b>(4-d)/2d$. The proof is based on the lace expansion and an adaptation of the inductive approach applied to the discretized contact process. We prove the existence of several critical exponents and show that they take on their respective mean-field values. The results in this paper provide crucial ingredients to prove convergence of the finite-dimensional distributions for the contact process towards those for the canonical measure of super-Brownian motion, which we defer to a sequel of this paper. The results in this paper also apply to oriented percolation, for which we reprove some of the results in \cite{hs01} and extend the results to the local mean-field setting described above when $d\leq4$.

An asymptotic expansion for the discrete harmonic potential

Abstract: We give two algorithms that allow to get arbitrary precision asymptotics for the harmonic potential of a random walk.

Mixing Times for Random Walks on Finite Lamplighter Groups

Abstract: Given a finite graph $G$, a vertex of the lamplighter graph $G^\diamondsuit=\mathbb {Z}_2 \wr G$ consists of a zero-one labeling of the vertices of $G$, and a marked vertex of $G$. For transitive $G$ we show that, up to constants, the relaxation time for simple random walk in $G^\diamondsuit$ is the maximal hitting time for simple random walk in $G$, while the mixing time in total variation on $G^\diamondsuit$ is the expected cover time on $G$. The mixing time in the uniform metric on $G^\diamondsuit$ admits a sharp threshold, and equals $|G|$ multiplied by the relaxation time on $G$, up to a factor of $\log |G|$. For $\mathbb {Z}_2 \wr \mathbb {Z}_n^2$, the lamplighter group over the discrete two dimensional torus, the relaxation time is of order $n^2 \log n$, the total variation mixing time is of order $n^2 \log^2 n$, and the uniform mixing time is of order $n^4$. For $\mathbb {Z}_2 \wr \mathbb {Z}_n^d$ when $d\geq 3$, the relaxation time is of order $n^d$, the total variation mixing time is of order $n^d \log n$, and the uniform mixing time is of order $n^{d+2}$. In particular, these three quantities are of different orders of magnitude.

The Beurling Estimate for a Class of Random Walks

Abstract: An estimate of Beurling states that if $K$ is a curve from $0$ to the unit circle in the complex plane, then the probability that a Brownian motion starting at $-\varepsilon$ reaches the unit circle without hitting the curve is bounded above by $c \varepsilon^{1/2}$. This estimate is very useful in analysis of boundary behavior of conformal maps, especially for connected but rough boundaries. The corresponding estimate for simple random walk was first proved by Kesten. In this note we extend this estimate to random walks with zero mean, finite $(3+\delta)$-moment.

On Some Degenerate Large Deviation Problems

Abstract: This paper concerns the issue of obtaining the large deviation principle for solutions of stochastic equations with possibly degenerate coefficients Specifically, we explore the potential of the methodology that consists in establishing exponential tightness and identifying the action functional via a maxingale problem In the author's earlier work it has been demonstrated that certain convergence properties of the predictable characteristics of semimartingales ensure both that exponential tightness holds and that every large deviation accumulation point is a solution to a maxingale problem The focus here is on the uniqueness for the maxingale problem It is first shown that under certain continuity hypotheses existence and uniqueness of a solution to a maxingale problem of diffusion type are equivalent to Luzin weak existence and uniqueness, respectively, for the associated idempotent Ito equation Consequently, if the idempotent equation has a unique Luzin weak solution, then the action functional is specified uniquely, so the large deviation principle follows Two kinds of application are considered Firstly, we obtain results on the logarithmic asymptotics of moderate deviations for stochastic equations with possibly degenerate diffusion coefficients which, as compared with earlier results, relax the growth conditions on the coefficients, permit certain non-Lipshitz-continuous coefficients, and allow the coefficients to depend on the entire past of the process and to be discontinuous functions of time The other application concerns multiple-server queues with impatient customers

Intrinsic Coupling on Riemannian Manifolds and Polyhedra

Abstract: Starting from a central limit theorem for geometric random walks we give an elementary construction of couplings between Brownian motions on Riemannian manifolds. This approach shows that cut locus phenomena are indeed inessential for Kendall's and Cranston's stochastic proof of gradient estimates for harmonic functions on Riemannian manifolds with lower curvature bounds. Moreover, since the method is based on an asymptotic quadruple inequality and a central limit theorem only it may be extended to certain non smooth spaces which we illustrate by the example of Riemannian polyhedra. Here we also recover the classical heat kernel gradient estimate which is well known from the smooth setting.

On Infection Spreading and Competition between Independent Random Walks

Abstract: We study the models of competition and spreading of infection for infinite systems of independent random walks. For the competition model, we investigate the question whether one of the spins prevails with probability one. For the infection spreading, we give sufficient conditions for recurrence and transience (i.e., whether the origin will be visited by infected particles infinitely often a.s.).

Hierarchical equilibria of branching populations

Abstract: . The objective of this paper is the study of the equilibrium behavior of a population on the hierarchical group $\Omega_N$ consisting of families of individuals undergoing critical branching random walk and in addition these families also develop according to a critical branching process. Strong transience of the random walk guarantees existence of an equilibrium for this two-level branching system. In the limit $N\to\infty$ (called the hierarchical mean field limit ), the equilibrium aggregated populations in a nested sequence of balls $B^{(N)}_\ell$ of hierarchical radius $\ell$ converge to a backward Markov chain on $\mathbb{R_+}$. This limiting Markov chain can be explicitly represented in terms of a cascade of subordinators which in turn makes possible a description of the genealogy of the population.

Reconstructing a Multicolor Random Scenery seen along a Random Walk Path with Bounded Jumps

Abstract: Kesten noticed that the scenery reconstruction method proposed by Matzinger in his PhD thesis relies heavily on the skip-free property of the random walk. He asked if one can still reconstruct an i.i.d. scenery seen along the path of a non-skip-free random walk. In this article, we positively answer this question. We prove that if there are enough colors and if the random walk is recurrent with at most bounded jumps, and if it can reach every integer, then one can almost surely reconstruct almost every scenery up to translations and reflections. Our reconstruction method works if there are more colors in the scenery than possible single steps for the random walk.

Percolation Transition for Some Excursion Sets

Abstract: We consider a random field $(X_n)_{n\in\mathbb{Z}^d}$ and investigate when the set $A_h=\{k\in\mathbb{Z}^d; \vert X_k\vert \ge h\}$ has infinite clusters. The main problem is to decide whether the critical level $$h_c=\sup\{h\in R : P(A_h\text{ has an infinite cluster })>0\}$$ is neither $0$ nor $+\infty$. Thus, we say that a percolation transition occurs. In a first time, we show that weakly dependent Gaussian fields satisfy to a well-known criterion implying the percolation transition. Then, we introduce a concept of percolation along reasonable paths and therefore prove a phenomenon of percolation transition for reasonable paths even for strongly dependent Gaussian fields. This allows to obtain some results of percolation transition for oriented percolation. Finally, we study some Gibbs states associated to a perturbation of a ferromagnetic quadratic interaction. At first, we show that a transition percolation occurs for superstable potentials. Next, we go to the the critical case and show that a transition percolation occurs for directed percolation when $d\ge 4$. We also note that the assumption of ferromagnetism can be relaxed when we deal with Gaussian Gibbs measures, i.e., when there is no perturbation of the quadratic interaction.

Multifractal Analysis of a Class of Additive Processes with Correlated Non-Stationary Increments

Abstract: We consider a family of stochastic processes built from infinite sums of independent positive random functions on $R_+$. Each of these functions increases linearly between two consecutive negative jumps, with the jump points following a Poisson point process on $R_+$. The motivation for studying these processes stems from the fact that they constitute simplified models for TCP traffic on the Internet. Such processes bear some analogy with Levy processes, but they are more complex in the sense that their increments are neither stationary nor independent. Nevertheless, we show that their multifractal behavior is very much the same as that of certain Levy processes. More precisely, we compute the Hausdorff multifractal spectrum of our processes, and find that it shares the shape of the spectrum of a typical Levy process. This result yields a theoretical basis to the empirical discovery of the multifractal nature of TCP traffic.

Small-time Behaviour of Lévy Processes

Abstract: In this paper a necesary and sufficient condition is established for the probability that a Levy process is positive at time $t$ to tend to 1 as $t$ tends to 0. This condition is expressed in terms of the characteristics of the process, and is also shown to be equivalent to two probabilistic statements about the behaviour of the process for small time $t$.

Countable Systems of Degenerate Stochastic Differential Equations with Applications to Super-Markov Chains

Abstract: We prove well-posedness of the martingale problem for an infinite-dimensional degenerate elliptic operator under appropriate Holder continuity conditions on the coefficients. These martingale problems include large population limits of branching particle systems on a countable state space in which the particle dynamics and branching rates may depend on the entire population in a Holder fashion. This extends an approach originally used by the authors in finite dimensions.

A Singular Parabolic Anderson Model

Abstract: We consider the heat equation with a singular random potential term. The potential is Gaussian with mean 0 and covariance given by a small constant times the inverse square of the distance. Solutions exist as singular measures, under suitable assumptions on the initial conditions and for sufficiently small noise. We investigate various properties of the solutions using such tools as scaling, self-duality and moment formulae. This model lies on the boundary between nonexistence and smooth solutions. It gives a new model, other than the superprocess, which has measure-valued solutions.

Coupling Iterated Kolmogorov Diffusions

Abstract: The Kolmogorov-1934 diffusion is the two-dimensional diffusion generated by real Brownian motion and its time integral. In this paper we construct successful co-adapted couplings for iterated Kolmogorov diffusions defined by adding iterated time integrals as further components to the original Kolmogorov diffusion. A Laplace-transform argument shows it is not possible successfully to couple all iterated time integrals at once; however we give an explicit construction of a successful co-adapted coupling method for Brownian motion, its time integral, and its twice-iterated time integral; and a more implicit construction of a successful co-adapted coupling method which works for finite sets of iterated time integrals.

A non-uniform bound for translated Poisson approximation

Abstract: Let $X_1, \ldots , X_n$ be independent, integer valued random variables, with $p^{\text{th}}$ moments, $p >2$, and let $W$ denote their sum. We prove bounds analogous to the classical non-uniform estimates of the error in the central limit theorem, but now, for approximation of ${\cal L}(W)$ by a translated Poisson distribution. The advantage is that the error bounds, which are often of order no worse than in the classical case, measure the accuracy in terms of total variation distance. In order to have good approximation in this sense, it is necessary for ${\cal L}(W)$ to be sufficiently smooth; this requirement is incorporated into the bounds by way of a parameter $\alpha$, which measures the average overlap between ${\cal L}(X_i)$ and ${\cal L}(X_i+1), 1 \le i \le n$.

Level Sets of Multiparameter Brownian Motions

Abstract: We use Girsanov's theorem to establish a conjecture of Khoshnevisan, Xiao and Zhong that $\phi(r) = r^{N-d/2} (\log \log (\frac{1}{r}))^{d/2}$ is the exact Hausdorff measure function for the zero level set of an $N$-parameter $d$-dimensional additive Brownian motion. We extend this result to a natural multiparameter version of Taylor and Wendel's theorem on the relationship between Brownian local time and the Hausdorff $\phi$-measure of the zero set.

Quasiderivatives and Interior Smoothness of Harmonic Functions Associated with Degenerate Diffusion Processes

Abstract: Proofs and two applications of two general results are given concerning the problem of establishing interior smoothness of probabilistic solutions of elliptic degenerate equations.

Asymptotic distributions and Berry-Esseen bounds for sums of record values

Abstract: Let $\{U_n, n \geq 1\}$ be independent uniformly distributed random variables, and $\{Y_n, n \geq 1\}$ be independent and identically distributed non-negative random variables with finite third moments. Denote $S_n = \sum_{i=1}^n Y_i$ and assume that $ (U_1, \cdots, U_n)$ and $S_{n+1}$ are independent for every fixed $n$. In this paper we obtain Berry-Esseen bounds for $\sum_{i=1}^n \psi(U_i S_{n+1})$, where $\psi$ is a non-negative function. As an application, we give Berry-Esseen bounds and asymptotic distributions for sums of record values.

Nonliner Filtering for Reflecting Diffusions in Random Enviroments via Nonparametric Estimation

Abstract: We study a nonlinear filtering problem in which the signal to be estimated is a reflecting diffusion in a random environment. Under the assumption that the observation noise is independent of the signal, we develop a nonparametric functional estimation method for finding workable approximate solutions to the conditional distributions of the signal state. Furthermore, we show that the pathwise average distance, per unit time, of the approximate filter from the optimal filter is asymptotically small in time. Also, we use simulations based upon a particle filter algorithm to show the efficiency of the method.

Stochastic differential equations with boundary conditions driven by a Poisson noise

Abstract: We consider one-dimensional stochastic differential equations with a boundary condition, driven by a Poisson process. We study existence and uniqueness of solutions and the absolute continuity of the law of the solution. In the case when the coefficients are linear, we give an explicit form of the solution and study the reciprocal process property.