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This paper considers a classical question of approximation of Brownian motion by a random walk in the setting of a sub-Riemannian manifold $M$. To construct such a random walk we first address several issues related to the degeneracy of…

Probability · Mathematics 2014-10-07 Maria Gordina , Thomas Laetsch

We study random walks on sub-Riemannian manifolds using the framework of retractions, i.e., approximations of normal geodesics. We show that such walks converge to the correct horizontal Brownian motion if normal geodesics are approximated…

Probability · Mathematics 2023-11-30 Michael Herrmann , Pit Neumann , Simon Schwarz , Anja Sturm , Max Wardetzky

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…

Probability · Mathematics 2019-05-21 Nicholas Georgiou , Aleksandar Mijatović , Andrew R. Wade

According to a version of Donsker's theorem, geodesic random walks on Riemannian manifolds converge to the respective Brownian motion. From a computational perspective, however, evaluating geodesics can be quite costly. We therefore…

Probability · Mathematics 2023-12-05 Simon Schwarz , Michael Herrmann , Anja Sturm , Max Wardetzky

We prove invariance principles for a mulditimensional random walk conditioned to stay in a cone. Our first result concerns convergence towards the Brownian meander in the cone. Furthermore, we prove functional convergence of $h$-transformed…

Probability · Mathematics 2015-11-03 Jetlir Duraj , Vitali Wachtel

We establish an invariance principle for a one-dimensional random walk in a dynamical random environment given by a speed-change exclusion process. The jump probabilities of the walk depend on the configuration of the exclusion in a finite…

Probability · Mathematics 2018-07-17 Milton Jara , Otávio Menezes

We show that geodesic random walks on a complete Finsler manifold of bounded geometry converge to a diffusion process which is, up to a drift, the Brownian motion corresponding to a Riemannian metric.

Differential Geometry · Mathematics 2022-12-07 Tianyu Ma , Vladimir S. Matveev , Ilya Pavlyukevich

We consider in this work a one parameter family of hypoelliptic diffusion processes on the unit tangent bundle $T^1 \mathcal M$ of a Riemannian manifold $(\mathcal M,g)$, collectively called kinetic Brownian motions, that are random…

Probability · Mathematics 2015-01-16 Jürgen Angst , Ismaël Bailleul , Camille Tardif

There are many classical random walk in random environment results that apply to ergodic random planar environments. We extend some of these results to random environments in which the length scale varies from place to place, so that the…

Probability · Mathematics 2021-06-11 Ewain Gwynne , Jason Miller , Scott Sheffield

This paper presents a unified geometric framework for Brownian motion on manifolds, encompassing intrinsic Riemannian manifolds, embedded submanifolds, and Lie groups. The approach constructs the stochastic differential equation by…

Probability · Mathematics 2025-10-24 Taeyoung Lee , Gregory S. Chirikjian

We study the Ergodic Properties of Random Walks in stationary ergodic environments without uniform ellipticity under a minimal assumption. There are two main components in our work. The first step is to adopt the arguments of Lawler to…

Probability · Mathematics 2026-02-03 Ayan Ghosh

We study a one-dimensional random walk among random conductances, with unbounded jumps. Assuming the ergodicity of the collection of conductances and a few other technical conditions (uniform ellipticity and polynomial bounds on the tails…

Probability · Mathematics 2012-10-08 Christophe Gallesco , Serguei Popov

Anderson's nonstandard construction of brownian motion as an infinitesimal random walk on the euclidean line is generalized to an Hausdorff riemannian manifold. A nonstandard Feynman-Kac formula holding on such an Hausdorff riemannian…

Mathematical Physics · Physics 2007-05-23 Gavriel Segre

We relate some basic constructions of stochastic analysis to differential geometry, via random walk approximations. We consider walks on both Riemannian and sub-Riemannian manifolds in which the steps consist of travel along either…

Differential Geometry · Mathematics 2017-05-15 Andrei Agrachev , Ugo Boscain , Robert Neel , Luca Rizzi

We study random walks on the integers driven by a sample of time-dependent nearest-neighbor conductances that are bounded but are permitted to vanish over time intervals of positive Lebesgue-length. Assuming only ergodicity of the…

Probability · Mathematics 2024-03-05 Marek Biskup , Minghao Pan

We prove large deviations principles (LDPs) for the perimeter and the area of the convex hull of a planar random walk with finite Laplace transform of its increments. We give explicit upper and lower bounds for the rate function of the…

Probability · Mathematics 2021-04-05 Arseniy Akopyan , Vladislav Vysotsky

The aim of this work is to study the convergence to equilibrium of an $(h,\rho)$-subelliptic random walk on a closed, connected Riemannian manifold $(M,g)$ associated with a subelliptic second-order differential operator $A$ on $M$. In such…

Analysis of PDEs · Mathematics 2025-11-25 Davide Tramontana

We consider a random walk on Z^d in an i.i.d. balanced random environment, that is a random walk for which the probability to jump from x to nearest neighbor x+e is the same as to nearest neighbor x-e. Assuming that the environment is…

Probability · Mathematics 2012-07-05 Noam Berger , Jean-Dominique Deuschel

We prove an invariance principle for the bridge of a random walk conditioned to stay positive, when the random walk is in the domain of attraction of a stable law, both in the discrete and in the absolutely continuous setting. This includes…

Probability · Mathematics 2012-10-10 Francesco Caravenna , Loïc Chaumont

A matrix random walk is a stochastic process of the form $B_k = (I+A_1)\cdots(I+A_k)$ where $A_j$ are independent ``step'' matrices in $\mathrm{M}_N(\mathbb{C})$. With the right entry-covariance, a rescaled matrix random walk converges to…

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