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Convergence rate to the stationary distribution for continuous-time Markov processes can be studied using Lyapunov functions. Recent work by the author provided explicit rates of convergence in special case of a reflected jump-diffusion on…

Probability · Mathematics 2020-03-25 Andrey Sarantsev

Identifying the full entropy production of active particles is a challenging task. We introduce a microscopic, thermodynamically consistent model, which leads to active Ornstein-Uhlenbeck statistics in the continuum limit. Our minimal model…

Statistical Mechanics · Physics 2023-12-15 Jonas H. Fritz , Udo Seifert

In this paper, we study the Ornstein-Uhlenbeck bridge process (i.e. the Ornstein-Uhlenbeck process conditioned to start and end at fixed points) constraints to have a fixed area under its path. We present both anticipative (in this case, we…

Statistical Mechanics · Physics 2017-10-11 Alain Mazzolo

We study properties of the (generalized) Dickman distribution with two parameters and the stationary solution of the Ornstein-Uhlenbeck stochastic differential equation driven by a Poisson process. In particular, we show that the marginal…

Probability · Mathematics 2025-06-19 Danijel Grahovac , Anastasiia Kovtun , Nikolai N. Leonenko , Andrey Pepelyshev

We provide new convergence guarantees in Wasserstein distance for diffusion-based generative models, covering both stochastic (DDPM-like) and deterministic (DDIM-like) sampling methods. We introduce a simple framework to analyze…

Machine Learning · Computer Science 2025-11-14 Eliot Beyler , Francis Bach

The Ornstein-Uhlenbeck process is interpreted as Brownian motion in a harmonic potential. This Gaussian Markov process has a bounded variance and admits a stationary probability distribution, in contrast to the standard Brownian motion. It…

Statistical Mechanics · Physics 2023-06-07 Pece Trajanovski , Petar Jolakoski , Kiril Zelenkovski , Alexander Iomin , Ljupco Kocarev , Trifce Sandev

We develop an infinite mixture model of Ornstein-Uhlenbeck(OU) processes for describing the optical variability of QSOs based on treating the variability as a stochastic process. This enables us to get the parameters of the power spectral…

Instrumentation and Methods for Astrophysics · Physics 2019-01-09 Tadafumi Takata , Yusuke Mukuta , Yoshihiko Mizumoto

We consider a transformed Ornstein-Uhlenbeck process model that can be a good candidate for modelling real-life processes characterized by a combination of time-reverting behaviour with heavy distribution tails. We begin with presenting the…

Probability · Mathematics 2011-03-01 K. Borovkov , G. Decrouez

The paper studies a class of Ornstein-Uhlenbeck processes on the classical Wiener space. These processes are associated with a diffusion type Dirichlet form whose corresponding diffusion operator is unbounded in the Cameron-Martin space. It…

Probability · Mathematics 2016-02-23 John Karlsson , Jörg-Uwe Löbus

We consider the extreme value statistics of correlated random variables that arise from a Langevin equation. Recently, it was shown that the extreme values of the Ornstein-Uhlenbeck process follow a different distribution than those…

Statistical Mechanics · Physics 2021-08-17 Lior Zarfaty , Eli Barkai , David A. Kessler

We study the full distribution of $A=\int_{0}^{T}x^{n}\left(t\right)dt$, $n=1,2,\dots$, where $x\left(t\right)$ is an Ornstein-Uhlenbeck process. We find that for $n>2$ the long-time ($T \to \infty$) scaling form of the distribution is of…

Statistical Mechanics · Physics 2022-01-21 Naftali R. Smith

We consider the statistical motion of a convex rigid body in a gas of N smaller (spherical) atoms close to thermodynamic equilibrium. Because the rigid body is much bigger and heavier, it undergoes a lot of collisions leading to small…

Analysis of PDEs · Mathematics 2018-07-04 Thierry Bodineau , Isabelle Gallagher , Laure Saint-Raymond

Diffusion models learn to reverse the progressive noising of a data distribution to create a generative model. However, the desired continuous nature of the noising process can be at odds with discrete data. To deal with this tension…

Machine Learning · Computer Science 2023-09-13 Griffin Floto , Thorsteinn Jonsson , Mihai Nica , Scott Sanner , Eric Zhengyu Zhu

We study the first-passage dynamics of a non-Markovian stochastic process with time-averaged feedback, which we model as a one-dimensional Ornstein--Uhlenbeck process wherein the particle drift is modified by the empirical mean of its…

Statistical Mechanics · Physics 2025-09-16 Francesco Coghi , Romain Duvezin , John S. Wettlaufer

In this paper, we analyze the use of the Ornstein-Uhlenbeck process to model dynamical systems subjected to bounded noisy perturbations. In order to discuss the main characteristics of this new approach we consider some basic models in…

Dynamical Systems · Mathematics 2024-01-17 Tomás Caraballo , Renato Colucci , Javier López-de-la-Cruz , Alain Rapaport

We consider processes of deterministic motions on $k$ copies of the star-like graph $S_k= K_{1,k}$ with $k$ edges which are perturbed by two stochastic mechanisms: one caused by interfaces located at the graphs' centers, the other…

Probability · Mathematics 2024-09-25 Adam Bobrowski , Elżbieta Ratajczyk

We develop here a stochastic framework for modeling and segmenting transient spindle-like oscillatory bursts in electroencephalogram (EEG) signals. At the modeling level, individual spindles are represented as path realizations of a…

Neurons and Cognition · Quantitative Biology 2025-12-13 C. Sun , D. Fettahoglu , D. Holcman

We characterise the nonequilibrium stationary state of a generic multivariate Ornstein-Uhlenbeck process involving $N$ degrees of freedom. The irreversibility of the process is encoded in the antisymmetric part of the Onsager matrix. The…

Statistical Mechanics · Physics 2018-12-19 Claude Godrèche , Jean-Marc Luck

Many physical and biological systems rely on the progression of material through multiple independent stages. In viral replication, for example, virions enter a cell to undergo a complex process comprising several disparate stages before…

Molecular Networks · Quantitative Biology 2024-04-03 Alexander P Browning , Adrianne L Jenner , Ruth E Baker , Philip K Maini

Front propagation in time dependent laminar flows is investigated in the limit of very fast reaction and very thin fronts, i.e. the so-called geometrical optics limit. In particular, we consider fronts evolving in time correlated random…

Chaotic Dynamics · Physics 2009-11-11 M. Chinappi , M. Cencini , A. Vulpiani