Abstract

We prove an invariance principle for a class of zero-drift spatially non-homogeneous random walks in ${\mathbb R}^d$, which may be recurrent in any dimension. The limit $\mathcal{X} $ is an elliptic martingale diffusion, which may be point-recurrent at the origin for any $d\geq 2$. To characterize $\mathcal{X} $, we introduce a (non-Euclidean) Riemannian metric on the unit sphere in ${\mathbb R}^d$ and use it to express a related spherical diffusion as a Brownian motion with drift. This representation allows us to establish the skew-product decomposition of the excursions of $\mathcal{X} $ and thus develop the excursion theory of $\mathcal{X} $ without appealing to the strong Markov property. This leads to the uniqueness in law of the stochastic differential equation for $\mathcal{X} $ in ${\mathbb R}^d$, whose coefficients are discontinuous at the origin. Using the Riemannian metric we can also detect whether the angular component of the excursions of $\mathcal{X} $ is time-reversible. If so, the excursions of $\mathcal{X} $ in ${\mathbb R}^d$ generalize the classical Pitman–Yor splitting-at-the-maximum property of Bessel excursions.

Highlights

  • A large class of spatially non-homogeneous zero-drift random walks (Markov chains) on Rd (d ≥ 2) was introduced in [9], where it was shown that such a walk may be transient or recurrent in any dimension d ≥ 2

  • Since the diffusion coefficient is discontinuous at 0, the proof of the uniqueness in law requires the development of the excursion theory of X before the strong Markov property can be established

  • As described in [9], the recurrence/transience of our non-homogeneous random walks is determined by the interplay between the radial and transverse components of the variance of the increments

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Summary

Introduction

A large class of spatially non-homogeneous zero-drift random walks (Markov chains) on Rd (d ≥ 2) was introduced in [9], where it was shown that such a walk may be transient or recurrent in any dimension d ≥ 2. Since the diffusion coefficient is discontinuous at 0, the proof of the uniqueness in law requires the development of the excursion theory of X before the strong Markov property can be established This step constitutes the main technical contribution of the paper (see Section 3.6 below) and provides an insight into the structure of the excursions of X. The choice of the square root of σ2 turns out to be relevant for the pathwise uniqueness of SDE (1.1), which may fail, generalizing to higher dimensions the example of Stroock and Yor [27] for complex BM These and other features of the law of X are described in more detail in Section 1.1 below.

The diffusion limit
Angular convergence and the first exit from large balls of the random walk
Assumptions and examples
Overview
The radial process
Marked Bessel excursions
Invariance principle with discontinuous coefficients
Full Text
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