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We develop a mixture model for transition density approximation, together with soft model selection, in the presence of noisy and heterogeneous nonlinear dynamics. Our model builds on the Gaussian mixture transition distribution (MTD) model…

Methodology · Statistics 2021-06-03 Matthew Heiner , Athanasios Kottas

A model has two main aims: predicting the behavior of a physical system and understanding its nature, that is how it works, at some desired level of abstraction. A promising recent approach to model building consists in deriving a…

Statistical Mechanics · Physics 2019-02-26 Marco Baldovin , Andrea Puglisi , Angelo Vulpiani

This paper introduces a new stochastic process with values in the set Z of integers with sign. The increments of process are Poisson differences and the dynamics has an autoregressive structure. We study the properties of the process and…

Methodology · Statistics 2020-02-12 Giulia Carallo , Roberto Casarin , Christian P. Robert

We present new simulation results on a hard sphere system at high densities. Using three-time correlations, we can account for the anomalous diffusion, which results from a homogeneous back-dragging effect. Furthermore, we calculate the…

Soft Condensed Matter · Physics 2007-05-23 Burkhard Doliwa , Andreas Heuer

In this paper we study macroscopic density equations in which the diffusion coefficient depends on a weighted spatial average of the density itself. We show that large differences (not present in the local density-dependence case) appear…

Statistical Mechanics · Physics 2009-11-11 Cristobal Lopez

Fractional Brownian motion and the fractional Langevin equation are models of anomalous diffusion processes characterized by long-range power-law correlations in time. We employ large-scale computer simulations to study these models in two…

Statistical Mechanics · Physics 2021-04-22 Thomas Vojta , Alex Warhover

This review article aims to stress and reunite some of the analytic formalism of the anomalous diffusive processes that have succeeded in their description. Also, it has the objective to discuss which of the new directions they have taken…

Statistical Mechanics · Physics 2019-05-28 Maike A. F. dos Santos

We consider a one-dimensional diffusion process with coefficients that are periodic outside of a finite 'interface region'. The question investigated in this article is the limiting long time / large scale behaviour of such a process under…

Probability · Mathematics 2010-05-14 Martin Hairer , Charles Manson

We consider a 1-dimensional Brownian motion whose diffusion coefficient varies when it crosses the origin. We study the long time behavior and we establish different regimes, depending on the variations of the diffusion coefficient:…

Probability · Mathematics 2016-11-28 Nicolas Meunier , Clément Mouhot , Raphaël Roux

Last year in [Phys. Rev. E 102, 042121 (2020)] the authors studied an overdamped dynamics of nonequilibrium noise driven Brownian particle dwelling in a spatially periodic potential and discovered a novel class of Brownian, yet non-Gaussian…

Statistical Mechanics · Physics 2021-12-22 Karol Białas , Jakub Spiechowicz

We investigate an intermittent stochastic process, in which the diffusive motion with time-dependent diffusion coefficient $D(t)\sim t^{\alpha-1}$, $\alpha>0$ (scaled Brownian motion), is stochastically reset to its initial position and…

Statistical Mechanics · Physics 2019-07-24 Anna S. Bodrova , Aleksei V. Chechkin , Igor M. Sokolov

In this thesis, we develop analytical methods to study out-of-equilibrium stochastic processes driven by colored noise, i.e., noise with temporal correlations. These non-Markovian processes pose significant analytical challenges compared to…

Statistical Mechanics · Physics 2025-08-07 Mathis Guéneau

We report on novel Brownian, yet non-Gaussian diffusion, in which the mean square displacement of the particle grows linearly with time, the probability density for the particle spreading is Gaussian-like, however, the probability density…

Statistical Mechanics · Physics 2020-10-28 K. Białas , J. Łuczka , P. Hänggi , J. Spiechowicz

Many complex systems are described by Langevin-type equations in which the noise exhibits long-range correlations and couples to the system in a state-dependent, multiplicative manner, leading to heterogeneous non-Markovian diffusion. Here,…

Statistical Mechanics · Physics 2026-05-13 David Santiago Quevedo , Felipe Segundo Abril-Bermúdez , Cristiane Morais Smith

We develop a class of non-Gaussian translation processes that extend classical stochastic differential equations (SDEs) by prescribing arbitrary absolutely continuous marginal distributions. Our approach uses a copula-based transformation…

Statistics Theory · Mathematics 2025-08-06 Robert Richardson , H. Dennis Tolley , Kenneth Kuttler

We present a stochastic method for reconstructing missing spatial and velocity data along the trajectories of small objects passively advected by turbulent flows with a wide range of temporal or spatial scales, such as small balloons in the…

Fluid Dynamics · Physics 2024-11-14 Tianyi Li , Luca Biferale , Fabio Bonaccorso , Michele Buzzicotti , Luca Centurioni

According to the classical theory of Brownian motion, the mean squared displacement of diffusing particles evolves linearly with time whereas the distribution of their displacements is Gaussian. However, recent experiments on mesoscopic…

Soft Condensed Matter · Physics 2021-08-24 J. M. Miotto , S. Pigolotti , A. V. Chechkin , S. Roldán-Vargas

Recent progress in experimental techniques such as single particle tracking allows to analyze both nonequilibrium properties and approach to equilibrium. There are examples showing that processes occurring at finite timescales are…

Statistical Mechanics · Physics 2025-01-24 I. G. Marchenko , I. I. Marchenko , J. Łuczka , J. Spiechowicz

The horizontal dynamics of a bouncing ball interacting with an irregular surface is investigated and is found to demonstrate behavior analogous to a random walk. Its stochastic character is substantiated by the calculation of a permutation…

Physics Education · Physics 2025-09-15 Luiz Antonio Barreiro

Diffusion models generate high-quality synthetic data. They operate by defining a continuous-time forward process which gradually adds Gaussian noise to data until fully corrupted. The corresponding reverse process progressively "denoises"…

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