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Stochastic averaging allows for the reduction of the dimension and complexity of stochastic dynamical systems with multiple time scales, replacing fast variables with statistically equivalent stochastic processes in order to analyze…

Probability · Mathematics 2015-02-25 William F. Thompson , Rachel A. Kuske , Adam H. Monahan

This article studies the fluctuation behaviour of the stochastic point vortex model with common noise. Using the martingale method combined with a localization argument, we prove that the sequence of fluctuation processes converges in…

Probability · Mathematics 2025-01-14 Yufei Shao , Xianliang Zhao

Piecewise-deterministic Markov processes combine continuous in time dynamics with jump events, the rates of which generally depend on the continuous variables and thus are not constants. This leads to a problem in a Monte-Carlo simulation…

Computational Physics · Physics 2025-01-14 Arkady Pikovsky

To obtain further insight on possible power law generalizations of Boltzmann equilibrium concepts, a stochastic collision model is investigated. We consider the dynamics of a tracer particle of mass $M$, undergoing elastic collisions with…

Statistical Mechanics · Physics 2009-11-10 Eli Barkai

In this paper, we study an ordinary differential equation with a degenerate global attractor at the origin, to which we add a white noise with a small parameter that regulates its intensity. Under general conditions, for any fixed…

Probability · Mathematics 2025-05-27 Gerardo Barrera , Conrado da Costa , Milton Jara

The study of time-inhomogeneous Markov jump processes is a traditional topic within probability theory that has recently attracted substantial attention in various applications. However, their flexibility also incurs a substantial…

Probability · Mathematics 2023-11-03 Martin Bladt , Oscar Peralta

Complex dynamical systems which are governed by anomalous diffusion often can be described by Langevin equations driven by L\'evy stable noise. In this article we generalize nonlinear stochastic differential equations driven by Gaussian…

Statistical Mechanics · Physics 2015-06-18 Rytis Kazakevicius , Julius Ruseckas

Dynamics near and far away from thermal equilibrium is studied within the framework of Langevin equations. A stochasticity-dissipation relation is proposed to emphasize the equal importance of the stochastic and deterministic forces in…

Classical Physics · Physics 2007-05-23 P. Ao

The big jump principle is a well established mathematical result for sums of independent and identically distributed random variables extracted from a fat tailed distribution. It states that the tail of the distribution of the sum is the…

Statistical Mechanics · Physics 2019-07-10 Alessandro Vezzani , Eli Barkai , Raffaella Burioni

We present a numerical method to produce stochastic dynamics according to the generalized Langevin equation with a non-stationary memory kernel. This type of dynamics occurs when a microscopic system with an explicitly time-dependent…

Statistical Mechanics · Physics 2022-11-30 Christoph Widder , Fabian Glatzel , Tanja Schilling

A continuously measured quantum system with multiple jump channels gives rise to a stochastic process described by random jump times and random emitted symbols, representing each jump channel. While much is known about the waiting time…

Quantum Physics · Physics 2023-06-21 Gabriel T. Landi

We consider a stochastic differential equation for a charged particle in a stochastic magnetic field, known as A-Langevin equation. The solution of the equation is found, and the Lagrange velocity correlation function is calculated in…

Chaotic Dynamics · Physics 2007-05-23 D. Lesnik , S. Gordienko , M. Neuer , K. -H. Spatschek

The long time dynamics of large particles trapped in two inhomogeneous turbulent shear flows is studied experimentally. Both flows present a common feature, a shear region that separates two colliding circulations, but with different…

Fluid Dynamics · Physics 2016-03-02 N Machicoane , M López-Caballero , L Fiabane , J-F Pinton , M Bourgoin , J Burguete , R Volk

We introduce a Langevin equation characterized by a time dependent drift. By assuming a temporal power-law dependence of the drift we show that a great variety of behavior is observed in the dynamics of the variance of the process. In…

Statistical Mechanics · Physics 2009-10-31 Fabrizio Lillo , Rosario N. Mantegna

In the last few decades, noise-induced large fluctuations and transition phenomena have garnered significant attention in a variety of scientific contexts. The concept of prehistory probability has been proposed within the framework of…

Probability · Mathematics 2026-03-10 Feng Zhao , Jinjie Zhu , Yang Li , Xianbin Liu , Dongping Jin

We introduce a constructive framework to learn effective Langevin equations from stationary time series. Unlike conventional approaches that require iterative calibration to match target statistics, our construction guarantees the observed…

Chaotic Dynamics · Physics 2026-02-16 Ludovico Theo Giorgini

Many stochastic physical systems evolve smoothly over time in the sense that the distribution of states changes regularly across time steps. The transition from current state to the next state can often be modeled as the combination of a…

Machine Learning · Computer Science 2026-05-29 Jules Berman , Tobias Blickhan , Benjamin Peherstorfer

We consider shot-noise processes with an impulse response written in terms of the logarithm of the ratio between current and event time (instead of the usual absolute time difference). We study its finite-time properties as well as its weak…

Probability · Mathematics 2026-05-05 Luisa Beghin , Lorenzo Cristofaro , Enrico Scalas

The measured time series from complex systems are renowned for their intricate stochastic behavior, characterized by random fluctuations stemming from external influences and nonlinear interactions. These fluctuations take diverse forms,…

Statistical Mechanics · Physics 2025-03-19 Pyei Phyo Lin , Matthias Wächter , Joachim Peinke , M. Reza Rahimi Tabar

This paper considers the problem of estimating the time auto-correlation function for a quantity that is defined in configuration space, given a knowledge of the mean-square displacement as function of time in configuration space. The…

Condensed Matter · Physics 2007-05-23 Jeppe C. Dyre