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Surprisingly the looking natural random walk leading to Brownian motion occurs to be often biased in a very subtle way: usually refers to only approximate fulfillment of thermodynamical principles like maximizing uncertainty. Recently, a…

Quantum Physics · Physics 2015-06-03 Jarek Duda

We prove an estimate for the probability that a simple random walk in a simply connected subset A of Z^2 starting on the boundary exits A at another specified boundary point. The estimates are uniform over all domains of a given inradius.…

Probability · Mathematics 2009-05-15 Michael J. Kozdron , Gregory F. Lawler

We derive P(M,t_m), the joint probability density of the maximum M and the time t_m at which this maximum is achieved for a class of constrained Brownian motions. In particular, we provide explicit results for excursions, meanders and…

Statistical Mechanics · Physics 2008-10-31 Satya. N. Majumdar , Julien Randon-Furling , Michael J. Kearney , Marc Yor

We establish the discrete approximation to Brownian motion with varying dimension (BMVD in abbreviation) by random walks. The setting is very similar to that in [11], but here we use a different method allowing us to get rid the…

Probability · Mathematics 2021-11-16 Shuwen Lou

We prove a conjecture of Lalley and Sellke [Ann. Probab. 15 (1987)] asserting that the empirical (time-averaged) distribution function of the maximum of branching Brownian motion converges almost surely to a double exponential, or Gumbel,…

Probability · Mathematics 2012-01-10 Louis-Pierre Arguin , Anton Bovier , Nicola Kistler

We propose a model of random walks on weighted graphs where the weights are interval valued, and connect it to reversible imprecise Markov chains. While the theory of imprecise Markov chains is now well established, this is a first attempt…

Optimization and Control · Mathematics 2016-09-20 Damjan Škulj

In recent decades, advancements in motion learning have enabled robots to acquire new skills and adapt to unseen conditions in both structured and unstructured environments. In practice, motion learning methods capture relevant patterns and…

Robotics · Computer Science 2023-08-21 Hadi Beik-Mohammadi , Søren Hauberg , Georgios Arvanitidis , Gerhard Neumann , Leonel Rozo

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

We offer an alternative viewpoint on Dyson's original paper regarding the application of Brownian motion to random matrix theory (RMT). In particular we show how one may use the same approach in order to study the stochastic motion in the…

Mathematical Physics · Physics 2015-03-24 Christopher H. Joyner , Uzy Smilansky

In this paper, we derive the distribution of a two-dimensional (complex) random walk in which the angle of each step is restricted to a subset of the circle. This setting appears in various domains, such as in over-the-air computation in…

Signal Processing · Electrical Eng. & Systems 2026-05-18 Karl-Ludwig Besser

We approximate the solution of some linear systems of SDEs driven by a fractional Brownian motion $B^H$ with Hurst parameter $H\in(\frac{1}{2},1)$ in the Wick--It\^{o} sense, including a geometric fractional Brownian motion. To this end, we…

Statistics Theory · Mathematics 2010-10-11 Christian Bender , Peter Parczewski

Donsker's invariance principle is shown to hold for random walks in rough path topology. As application, we obtain Donsker-type weak limit theorems for stochastic integrals and differential equations.

Probability · Mathematics 2008-10-16 Emmanuel Breuillard , Peter Friz , Martin Huesmann

Consider a generic triangle in the upper half of the complex plane with one side on the real line. This paper presents a tailored construction of a discrete random walk whose continuum limit is a Brownian motion in the triangle, reflected…

Probability · Mathematics 2007-06-13 Wouter Kager

We examine a wide class of stochastic approximation algorithms for solving (stochastic) nonlinear problems on Riemannian manifolds. Such algorithms arise naturally in the study of Riemannian optimization, game theory and optimal transport,…

Optimization and Control · Mathematics 2022-12-29 Mohammad Reza Karimi , Ya-Ping Hsieh , Panayotis Mertikopoulos , Andreas Krause

This survey is concerned with random walks on mapping class groups. We illustrate how the actions of mapping class groups on Teichm\"uller spaces or curve complexes reveal the nature of random walks, and vice versa. Our emphasis is on the…

Geometric Topology · Mathematics 2021-10-12 Inhyeok Choi , Hyungryul Baik

Walk on Spheres algorithms leverage properties of Brownian Motion to create Monte Carlo estimates of solutions to a class of elliptic partial differential equations. We propose a new caching strategy which leverages the continuity of paths…

Computational Physics · Physics 2025-04-10 Michael Czekanski , Benjamin Faber , Margaret Fairborn , Adelle Wright , David Bindel

We introduce a simulation-based, amortised Bayesian inference scheme to infer the parameters of random walks. Our approach learns the posterior distribution of the walks' parameters with a likelihood-free method. In the first step a graph…

Machine Learning · Computer Science 2022-12-07 Hippolyte Verdier , François Laurent , Alhassan Cassé , Christian Vestergaard , Jean-Baptiste Masson

We prove that stochastic replicator dynamics can be interpreted as intrinsic Brownian motion on the simplex equipped the Aitchison geometry. As an immediate consequence we derive three approximation results in the spirit of Wong-Zakai…

Probability · Mathematics 2020-08-13 Tobias Lehmann

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

The aim of this paper is to represent any continuous local martingale as an almost sure limit of a nested sequence of simple, symmetric random walks, time changed by a discrete quadratic variation process. One basis of this is a similar…

Probability · Mathematics 2010-08-10 Balazs Szekely , Tamas Szabados