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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

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

On Sasakian manifolds with their naturally occurring sub-Riemannian structure, we consider parallel and mirror maps along geodesics of a taming Riemannian metric. We show that these transport maps have well-defined limits outside the…

Differential Geometry · Mathematics 2022-12-16 Fabrice Baudoin , Erlend Grong , Robert Neel , Anton Thalmaier

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 a certain class of Riemannian submersions $\pi : N \to M$ and study lifted geodesic random walks from the base manifold $M$ to the total manifold $N$. Under appropriate conditions on the distribution of the speed of the geodesic…

Probability · Mathematics 2023-10-03 Jonathan Junné , Frank Redig , Rik Versendaal

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

Cubical complexes are metric spaces constructed by gluing together unit cubes in an analogous way to the construction of simplicial complexes. We construct Brownian motion on such spaces, define random walks, and prove that the transition…

Populations and Evolution · Quantitative Biology 2019-05-23 Tom M. W. Nye

We construct a model of Brownian Motion on a pseudo-Riemannian manifold associated with general relativity. There are two aspects of the problem: The first is to define a sequence of stopping times associated with the Brownian "kicks" or…

General Physics · Physics 2013-04-02 Paul O'Hara , Lamberto Rondoni

In this note, we show that sub-Riemannian manifolds can contain branching normal minimizing geodesics. This phenomenon occurs if and only if a normal geodesic has a discontinuity in its rank at a non-zero time, which in particular for a…

Differential Geometry · Mathematics 2020-09-28 Thomas Mietton , Luca Rizzi

We consider the symmetric exclusion process on suitable random grids that approximate a compact Riemannian manifold. We prove that a class of random walks on these random grids converge to Brownian motion on the manifold. We then consider…

Probability · Mathematics 2020-01-08 Bart van Ginkel , Frank Redig

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

In this article, we show a result of approximation in law to subfractional Brownian motion, with $H>\frac{1}{2}$, in the Skorohod topology. The construction of these approximations is based on a sequence of I.I.D random variables

Probability · Mathematics 2014-01-17 Hongshuai Dai

In many robot motion planning problems, task objectives and physical constraints induce non-Euclidean geometry on the configuration space, yet many planners operate using Euclidean distances that ignore this structure. We address the…

Robotics · Computer Science 2026-05-15 Phone Thiha Kyaw , Jonathan Kelly

Consider a one dimensional simple random walk $X=(X_n)_{n\geq0}$. We form a new simple symmetric random walk $Y=(Y_n)_{n\geq0}$ by taking sums of products of the increments of $X$ and study the two-dimensional walk…

Probability · Mathematics 2015-08-18 Andrea Collevecchio , Kais Hamza , Meng Shi

In the present paper we show that the geodesic flows of a sub-Riemannian metric and that of a Riemannian extension commute if and only if the extended metric is parallel with respect to a certain connection. This helps us to describe the…

Differential Geometry · Mathematics 2015-02-24 Mauricio Godoy Molina , Erlend Grong

There is a close connection between intersections of Brownian motion paths and percolation on trees. Recently, ideas from probability on trees were an important component of the multifractal analysis of Brownian occupation measure, in joint…

Probability · Mathematics 2007-05-23 Yuval Peres

We study the radial part of sub-Riemannian Brownian motion in the context of totally geodesic foliations. It\^o's formula is proved for the radial processes associated to Riemannian distances approximating the Riemannian one. We deduce very…

Probability · Mathematics 2020-02-10 Fabrice Baudoin , Erlend Grong , Kazumasa Kuwada , Robert Neel , Anton Thalmaier

We analyze convergence of gradient-descent methods on Riemannian manifolds. In particular, we study randomization of Riemannian gradient algorithms for minimizing smooth cost functions (of Morse-Bott type). We prove that randomized gradient…

Optimization and Control · Mathematics 2025-07-08 Emanuel Malvetti , Christian Arenz , Gunther Dirr , Thomas Schulte-Herbrüggen

In this article it is shown that the Brownian motion on the continuum random tree is the scaling limit of the simple random walks on any family of discrete $n$-vertex ordered graph trees whose search-depth functions converge to the Brownian…

Probability · Mathematics 2012-10-24 David Croydon

Riemannian optimization uses local methods to solve optimization problems whose constraint set is a smooth manifold. A linear step along some descent direction usually leaves the constraints, and hence retraction maps are used to…

Statistics Theory · Mathematics 2023-01-19 Alexander Heaton , Matthias Himmelmann
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