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In this work, we are interested in building the fully discrete scheme for stochastic fractional diffusion equation driven by fractional Brownian sheet which is temporally and spatially fractional with Hurst parameters $H_{1}, H_{2}…

Numerical Analysis · Mathematics 2022-01-27 Daxin Nie , Jing Sun , Weihua Deng

We obtain the first probabilistic proof of continuous differentiability of time-dependent optimal boundaries in optimal stopping problems. The underlying stochastic dynamics is a one-dimensional, time-inhomogeneous diffusion. The gain…

Probability · Mathematics 2024-05-28 Tiziano De Angelis , Damien Lamberton

We study the long-time behavior of underdamped Brownian particle moving through a viscous medium and in a systematic potential, when it is subjected to a space-dependent high-frequency periodic force. When the frequency is very large, much…

Statistical Mechanics · Physics 2009-11-11 Malay Bandyopadhyay , Sushanta Dattagupta , Monamie Sanyal

We introduce the stochastic process of incremental multifractional Brownian motion (IMFBM), which locally behaves like fractional Brownian motion with a given local Hurst exponent and diffusivity. When these parameters change as function of…

Statistical Mechanics · Physics 2023-07-27 Jakub Slezak , Ralf Metzler

This paper considers the motion of an object subjected to dry friction and an external random force. The objective is to characterize the role of the correlation time of the external random force. We develop efficient stochastic simulation…

Statistical Mechanics · Physics 2023-09-26 Josselin Garnier , Laurent Mertz

Let $B^H=\{B^H(t),t\in{{\mathbb{R}}_+^N}\}$ be an $(N,d)$-fractional Brownian sheet with index $H=(H_1,...,H_N)\in(0,1)^N$ defined by $B^H(t)=(B^H_1(t),...,B^H_d(t)) (t\in {\mathbb{R}}_+^N),$ where $B^H_1,...,B^H_d$ are independent copies…

Probability · Mathematics 2008-08-25 Antoine Ayache , Dongsheng Wu , Yimin Xiao

Motivated by queues with many servers, we study Brownian steady-state approximations for continuous time Markov chains (CTMCs). Our approximations are based on diffusion models (rather than a diffusion limit) whose steady-state, we prove,…

Probability · Mathematics 2014-09-12 Itai Gurvich

This paper establishes the convergence of a time-steeping scheme for time fractional diffusion problems with nonsmooth data. We first analyze the regularity of the model problem with nonsmooth data, and then prove that the time-steeping…

Numerical Analysis · Mathematics 2018-04-30 Binjie Li , Hao Luo , Xiaoping Xie

We present a formalism for obtaining the statistical properties of functionals and inverse functionals of the paths of a particle diffusing in a one-dimensional quenched random potential. We demonstrate the implementation of the formalism…

Statistical Mechanics · Physics 2007-05-23 Sanjib Sabhapandit , Satya N. Majumdar , Alain Comtet

The (conditional or unconditional) distribution of the continuous scan statistic in a one-dimensional Poisson process may be approximated by that of a discrete analogue via time discretization (to be referred to as the discrete…

Probability · Mathematics 2016-02-09 Yi-Ching Yao , Daniel Wei-Chung Miao , Xenos Chang-Shuo Lin

The subject of this paper is to prove a functional weak invariance principle for the local time of a process generated by a Gibbs-Markov map. More precisely, let $\left(X,\mathcal{B},m,T,\alpha\right)$ is a mixing, probability preserving…

Dynamical Systems · Mathematics 2014-06-18 Michael Bromberg

In this paper, we study the existence and (H\"older) regularity of local times of stochastic differential equations driven by fractional Brownian motions. In particular, we show that in one dimension and in the rough case H<1/2, the…

Probability · Mathematics 2016-02-24 Shuwen Lou , Cheng Ouyang

Through a regularization procedure, few approximation schemes of the local time of a large class of one dimensional processes are given. We mainly consider the local time of continuous semimartingales and reversible diffusions, and the…

Probability · Mathematics 2007-09-05 Blandine Berard Bergery , Pierre Vallois

The effective diffusivity of Brownian tracer particles confined in periodic micro-channels is smaller than the microscopic diffusivity due to entropic trapping. Here, we study diffusion in two-dimensional periodic channels whose…

Statistical Mechanics · Physics 2019-05-29 M. Mangeat , T. Guérin , D. S. Dean

We study the estimation of the value function for continuous-time Markov diffusion processes using a single, discretely observed ergodic trajectory. Our work provides non-asymptotic statistical guarantees for the least-squares…

Machine Learning · Computer Science 2025-02-07 Wenlong Mou

We introduce numerical methods for simulating the diffusive motion of rigid bodies of arbitrary shape immersed in a viscous fluid. We parameterize the orientation of the bodies using normalized quaternions, which are numerically robust,…

Soft Condensed Matter · Physics 2015-10-28 Steven Delong , Florencio Balboa Usabiaga , Aleksandar Donev

Dirichlet processes and their extensions have reached a great popularity in Bayesian nonparametric statistics. They have also been introduced for spatial and spatio-temporal data, as a tool to analyze and predict surfaces. A popular…

Statistics Theory · Mathematics 2023-03-31 Clara Grazian

We study the exit-time from a domain of a self-interacting diffusion, where the Brownian motion is replaced by $\sigma B_t$ for a constant $\sigma$. The first part of this work consists in showing that the rate of convergence (of the…

Probability · Mathematics 2022-01-26 Ashot Aleksian , Pierre Del Moral , Aline Kurtzmann , Julian Tugaut

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining…

Numerical Analysis · Mathematics 2020-11-12 S. Baars , J. P. Viebahn , T. E. Mulder , C. Kuehn , F. W. Wubs , H. A. Dijkstra

Consistency models, which were proposed to mitigate the high computational overhead during the sampling phase of diffusion models, facilitate single-step sampling while attaining state-of-the-art empirical performance. When integrated into…

Machine Learning · Statistics 2024-02-13 Gen Li , Zhihan Huang , Yuting Wei