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We present the Markovian quantum master equation describing rotational decoherence, friction, diffusion, and thermalization of planar, linear, and asymmetric rotors in contact with a thermal environment. It describes how an arbitrary…

Quantum Physics · Physics 2018-07-27 Benjamin A. Stickler , Björn Schrinski , Klaus Hornberger

Continuous Time Markov Chains, Hawkes processes and many other interesting processes can be described as solution of stochastic differential equations driven by Poisson measures. Previous works, using the Stein's method, give the…

Probability · Mathematics 2026-04-02 Eustache Besançon , Laure Coutin , Laurent Decreusefond , Pascal Moyal

We find explicit upper bounds for the density of marginals of continuous diffusions where we assume that the diffusion coefficient is constant and the drift is solely assumed to be progressively measurable and locally bounded. In one…

Probability · Mathematics 2024-10-16 Paul Krühner , Shijie Xu

The long time behavior of an absorbed Markov process is well described by the limiting distribution of the process conditioned to not be killed when it is observed. Our aim is to give an approximation's method of this limit, when the…

Probability · Mathematics 2009-05-25 Denis Villemonais

We prove the convergence of the law of grid-valued random walks, which can be seen as time-space Markov chains, to the law of a general diffusion process. This includes processes with sticky features, reflecting or absorbing boundaries and…

Probability · Mathematics 2024-11-15 Alexis Anagnostakis , Antoine Lejay , Denis Villemonais

In the paper, the Kolmogorov distance is used to study the Smoluchowski-Kramers approximation for diffusions with jumps. The convergence rate is derived by Malliavin calculus.

Probability · Mathematics 2024-03-07 Chungang Shi

The Markov chain approximation of a one-dimensional symmetric diffusion is investigated in this paper. Given an irreducible reflecting diffusion on a closed interval with scale function $s$ and speed measure $m$, the approximating Markov…

Probability · Mathematics 2020-04-16 Xiaodan Li , Jiangang Ying

Cyclic structure and dynamics are of great interest in both the fields of stochastic processes and nonequilibrium statistical physics. In this paper, we find a new symmetry of the Brownian motion named as the quasi-time-reversal invariance.…

Probability · Mathematics 2017-04-27 Hao Ge , Chen Jia , Da-Quan Jiang

Ramaswami showed recently that standard Brownian motion arises as the limit of a family of Markov-modulated linear fluid processes. We pursue this analysis with a fluid approximation for Markov-modulated Brownian motion. Furthermore, we…

Probability · Mathematics 2014-07-22 Guy Latouche , Giang T. Nguyen

Upon almost-every realisation of the Brownian continuum random tree (CRT), it is possible to define a canonical diffusion process or `Brownian motion'. The main result of this article establishes that the cover time of the Brownian motion…

Probability · Mathematics 2025-09-30 George Andriopoulos , David A. Croydon , Vlad Margarint , Laurent Menard

Einstein's explanation of Brownian motion provided one of the cornerstones which underlie the modern approaches to stochastic processes. His approach is based on a random walk picture and is valid for Markovian processes lacking long-term…

Statistical Mechanics · Physics 2009-11-10 I. M. Sokolov , J. Klafter

In this paper we identify the Fokker-Planck equation for (reflected) Sticky Brownian Motion as a Wasserstein gradient flow in the space of probability measures. The driving functional is the relative entropy with respect to a non-standard…

Analysis of PDEs · Mathematics 2025-01-27 Jean-Baptiste Casteras , Léonard Monsaingeon , Filippo Santambrogio

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

The aim of this paper is to study the asymptotic behaviour of a class of self- attracting motions on R^d . Using stochastic approximation methods, these processes have already been studied by Bena\"im, Ledoux and Raimond (2002) in a compact…

Probability · Mathematics 2010-06-01 Victor Kleptsyn , Aline Kurtzmann

This article presents a review of some old and new results on the long time behavior of reflected diffusions. First, we present a summary of prior results on construction, ergodicity and geometric ergodicity of reflected diffusions in the…

Probability · Mathematics 2022-08-08 Sayan Banerjee , Amarjit Budhiraja

In this paper we study the diffusion approximation of a swarming model given by a system of interacting Langevin equations with nonlinear friction. The diffusion approximation requires the calculation of the drift and diffusion coefficients…

Numerical Analysis · Mathematics 2015-05-08 V. Bonnaillie-Noël , J. A. Carrillo , T. Goudon , G. A. Pavliotis

Measurements of protein motion in living cells and membranes consistently report transient anomalous diffusion (subdiffusion) which converges back to a Brownian motion with reduced diffusion coefficient at long times, after the anomalous…

Quantitative Methods · Quantitative Biology 2015-06-05 Hédi Soula , Bertrand Caré , Guillaume Beslon , Hugues Berry

We develop diffusion models for time-varying correlation using stochastic processes defined on the unit circle. Specifically, we study Brownian motion on the circle and the von Mises diffusion, and propose their use as continuous-time…

Statistics Theory · Mathematics 2026-01-05 Sourav Majumdar , Arnab Kumar Laha

The present work investigates the asymptotic behaviors, at the zero-noise limit, of the first collision-time and first collision-location related to a pair of self-stabilizing diffusions and of their related particle approximations. These…

Probability · Mathematics 2022-06-13 Jean-Francois Jabir , Julian Tugaut

This paper develops a new technique for the path approximation of one-dimensional stochastic processes, more precisely the Brownian motion and families of stochastic differential equations sharply linked to the Brownian motion (usually…

Probability · Mathematics 2020-12-16 Madalina Deaconu , Samuel Herrmann