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We prove a limit theorem for an integral functional of a Markov process. The Markovian dynamics is characterized by a linear Boltzmann equation modeling a one-dimensional test particle of mass $\lambda^{-1}\gg 1$ in an external periodic…

Mathematical Physics · Physics 2013-07-22 Jeremy Clark

We study the recovery of one-dimensional semipermeable barriers for a stochastic process in a planar domain. The considered process acts like Brownian motion when away from the barriers and is reflected upon contact until a sufficient but…

Probability · Mathematics 2024-12-20 Alexander Van Werde , Jaron Sanders

In this paper, we develop and analyze an integral fixed-time sliding mode control method for a scenario in which the system model is only partially known, utilizing Gaussian processes. We present two theorems on fixed-time convergence. The…

Systems and Control · Electrical Eng. & Systems 2025-05-30 Chaimae El Mortajinea , Moussa Labbadib , Adnane Saoudc , Mostafa Bouzia

We investigate a functional limit theorem (homogenization) for Reflected Stochastic Differential Equations on a half-plane with stationary coefficients when it is necessary to analyze both the effective Brownian motion and the effective…

Probability · Mathematics 2009-09-18 Remi Rhodes

We study the scaling limits of genealogical trees arising from Cannings models. Under suitable moment conditions, we show that the rescaled contour and height functions converge to a time change of Brownian motion conditioned on a given…

Probability · Mathematics 2026-02-04 Xiaodan Li , Chengshi Wang , Yushu Zheng

We map the problem of diffusion in the quenched trap model onto a new stochastic process: Brownian motion which is terminated at the coverage "time" ${\cal S}_\alpha=\sum_{x=-\infty} ^\infty (n_x)^\alpha$ with $n_x$ being the number of…

Statistical Mechanics · Physics 2015-06-05 Stas Burov , Eli Barkai

We introduce a technique to merge two biased Brownian motions into a single regular process. The outcome follows a stochastic differential equation with a constant diffusion coefficient and a non-linear drift. The emerging stochastic…

Probability · Mathematics 2023-04-03 Miquel Montero

In this paper we discuss the process convergence of the time dependent fluctuations of linear eigenvalue statistics of random circulant matrices with independent Brownian motion entries, as the dimension of the matrix tends to $\infty $.…

Probability · Mathematics 2019-09-04 Shambhu Nath Maurya , Koushik Saha

We present a detailed study of a simple quantum stochastic process, the quantum phase space Brownian motion, which we obtain as the Markovian limit of a simple model of open quantum system. We show that this physical description of the…

Mathematical Physics · Physics 2015-05-27 Michel Bauer , Denis Bernard

We show the appearance of spatiotemporal stochastic resonance in the Swift-Hohenberg equation. This phenomenon emerges when a control parameter varies periodically in time around the bifurcation point. By using general scaling arguments and…

Condensed Matter · Physics 2016-08-15 J. M. G. Vilar , J. M. Rubí

We study the long-time asymptotics of the probability P_t that the Riemann-Liouville fractional Brownian motion with Hurst index H does not escape from a fixed interval [-L,L] up to time t. We show that for any H \in ]0,1], for both…

Statistical Mechanics · Physics 2008-01-07 G. Oshanin

The linear fractional stable motion generalizes two prominent classes of stochastic processes, namely stable L\'evy processes, and fractional Brownian motion. For this reason it may be regarded as a basic building block for continuous time…

Statistics Theory · Mathematics 2022-08-17 Fabian Mies , Mark Podolskij

We study a system of reflected Brownian motions on the positive half-line in which each particle has a drift toward the origin determined by the local times at the origin of all the particles. If this local time drift is too strong, such…

Probability · Mathematics 2026-02-12 Graeme Baker , Ben Hambly , Philipp Jettkant

In this article, we analyze three classes of time-reversal of a Markov process with Gaussian noise on a manifold. We first unveil a commutativity constraint for the most general of these time-reversals to be well defined. Then we give a…

Statistical Mechanics · Physics 2024-08-09 Jérémy O'Byrne , Michael E. Cates

We study a model of $ N $ mutually repellent Brownian motions under confinement to stay in some bounded region of space. Our model is defined in terms of a transformed path measure under a trap Hamiltonian, which prevents the motions from…

Probability · Mathematics 2007-05-23 Stefan Adams , Jean-Bernard Bru , Wolfgang Koenig

We consider a finite or countable collection of one-dimensional Brownian particles whose dynamics at any point in time is determined by their rank in the entire particle system. Using Transportation Cost Inequalities for stochastic…

Probability · Mathematics 2010-11-11 Soumik Pal , Mykhaylo Shkolnikov

This work develops a comprehensive mathematical theory for a class of stochastic processes whose local regularity adapts dynamically in response to their own state. We first introduce and rigorously analyze a time-varying fractional…

Probability · Mathematics 2025-12-22 Jiahao Jiang

We exhibit some explicit co-adapted couplings for n-dimensional Brownian motion and all its Levy stochastic areas. In the two-dimensional case we show how to derive exact asymptotics for the coupling time under various mixed coupling…

Probability · Mathematics 2010-02-24 Wilfrid S. Kendall

A Brownian time process is a Markov process subordinated to the absolute value of an independent one-dimensional Brownian motion. Its transition densities solve an initial value problem involving the square of the generator of the original…

Probability · Mathematics 2009-06-25 Boris Baeumer , Mark M. Meerschaert , Erkan Nane

In this paper, we prove that if a sequence of electrical networks converges in the local Gromov-Hausdorff topology and satisfies a non-explosion condition, then the associated Bouchaud trap models (BTMs) also converge and exhibit aging.…

Probability · Mathematics 2024-12-12 Ryoichiro Noda