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Via a Dirichlet form extension theorem and making full use of two-sided heat kernel estimates, we establish quenched invariance principles for random walks in random environments with a boundary. In particular, we prove that the random walk…

Probability · Mathematics 2015-09-10 Zhen-Qing Chen , David A. Croydon , Takashi Kumagai

In this paper, we will present a strong (or pathwise) approximation of standard Brownian motion by a class of orthogonal polynomials. The coefficients that are obtained from the expansion of Brownian motion in this polynomial basis are…

Numerical Analysis · Mathematics 2020-05-21 James Foster , Terry Lyons , Harald Oberhauser

In this paper, we will first give the numerical simulation of the sub-fractional Brownian motion through the relation of fractional Brownian motion instead of its representation of random walk. In order to verify the rationality of this…

Probability · Mathematics 2021-01-11 Chunhao Cai , Qinghua Wang , Weilin Xiao

In this article we show a robustness theorem for controlled stochastic differential equations driven by approximations of Brownian motion. Often, Brownian motion is used as an idealized model of a diffusion where approximations such as…

Optimization and Control · Mathematics 2023-12-07 Somnath Pradhan , Zachary Selk , Serdar Yüksel

In this paper, we consider two skew Brownian motions, driven by the same Brownian motion, with different starting points and different skewness coefficients. We show that we can describe the evolution of the distance between the two…

Probability · Mathematics 2011-01-26 Arnaud Gloter , Miguel Martinez

We extend to Markov-modulated Brownian motion (MMBM) the renewal approach which has been successfully applied to the analysis of Markov-modulated fluid models. It has recently been shown that MMBM may be expressed as the limit of a…

Probability · Mathematics 2014-03-12 Guy Latouche , Giang T. Nguyen

We show that the distribution of the square of the supremum of reflected fractional Brownian motion up to time a, with Hurst parameter-H greater than 1/2, is related to the distribution of its hitting time to level $1,$ using the self…

Probability · Mathematics 2012-08-14 Ceren Vardar

Sub-fractional Brownian motion is a process analogous to fractional Brownian motion but without stationary increments. In \cite{GGL1} we proved a strong uniform approximation with a rate of convergence for fractional Brownian motion by…

Probability · Mathematics 2012-02-09 Johanna Garzon , Luis G. Gorostiza , Jorge A. Leon

We study Markov chains on $\mathbb Z^m$, $m\geq 2$, that behave like a standard symmetric random walk outside of the hyperplane (membrane) $H=\{0\}\times \mathbb Z^{m-1}$. The transition probabilities on the membrane $H$ are periodic and…

Probability · Mathematics 2021-08-05 V. Bogdanskii , I. Pavlyukevich , A. Pilipenko

In this paper we consider the random walk approximation of the solution of a Markovian BSDE whose terminal condition is a locally H{\"o}lder continuous function of the Brownian motion. We state the rate of the L 2-convergence of the…

Probability · Mathematics 2018-09-17 Christel Geiss , Céline Labart , Antti Luoto

We study differential equations with a linear, path dependent drift and discrete delay in the diffusion term driven by a $\gamma$-H\"older rough path for $\gamma > \frac{1}{3}$. We prove well-posedness of these systems and establish a…

Probability · Mathematics 2024-11-08 Mazyar Ghani Varzaneh , Sebastian Riedel

This work proposes a method for the two-dimensional simulation of Brownian particles in a fluid with restrictions. The method is based on simple numerical rules between two matrices. One of the matrix represent the identification of all…

Statistical Mechanics · Physics 2012-04-24 Eric Plaza

The signature is a collection of iterated integrals describing the "shape" of a path. It appears naturally in the Taylor expansions of controlled differential equations and, as a consequence, is arguably the central object within rough path…

Numerical Analysis · Mathematics 2025-10-31 James Foster

Let $\{B_t,t\geq0\}$ be a d-dimensional Brownian motion. We prove that the approximation of the higher derivative of renormalized self-intersection local time $$…

Probability · Mathematics 2024-03-18 Xiaoyan Xu , Xianye Yu

We present a numerical framework for approximating the $\mu$-domain in the planar Skorokhod embedding problem PSEP, recently introduced in \cite{gross2019}. We show that under weak convergence of a sequence of probability measures…

Probability · Mathematics 2026-05-26 Maher Boudabra , Mrabet Becher , Fathi Haggui

We point out a precise connection between Brownian motion, Chern-Simons theory on S^3, and 2d Yang-Mills theory on the cylinder. The probability of reunion for N vicious walkers on a line gives the partition function of Chern-Simons theory…

High Energy Physics - Theory · Physics 2009-11-10 Sebastian de Haro , Miguel Tierz

Let $d\geq 2$. In this paper, we investigate the following stochastic differential equation (SDE) in ${\mathbb R}^d$ driven by Brownian motion $$ {\rm d} X_t=b(t,X_t){\rm d} t+\sqrt{2}{\rm d} W_t, $$ where $b$ belongs to the space ${\mathbb…

Probability · Mathematics 2025-08-05 Zimo Hao , Xicheng Zhang

We study the second-order asymptotics around the superdiffusive strong law~\cite{MMW} of a multidimensional driftless diffusion with oblique reflection from the boundary in a generalised parabolic domain. In the unbounded direction we prove…

Probability · Mathematics 2024-12-20 Aleksandar Mijatović , Isao Sauzedde , Andrew Wade

In this paper we introduce a new method for the simulation of the exit time and position of a $\delta$-dimensional Brownian motion from a domain. The main interest of our method is that it avoids splitting time schemes as well as inversion…

Probability · Mathematics 2015-10-19 Madalina Deaconu , Samuel Herrmann , Sylvain Maire

Diffusion models have become the go-to method for large-scale generative models in real-world applications. These applications often involve data distributions confined within bounded domains, typically requiring ad-hoc thresholding…

Machine Learning · Statistics 2024-01-09 Wei Deng , Yu Chen , Nicole Tianjiao Yang , Hengrong Du , Qi Feng , Ricky T. Q. Chen
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