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Related papers: Anomalous Diffusion and the Generalized Langevin E…

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In this paper, we study a non-Markovian generalized relativistic Langevin equation (GRLE). We show that when the memory kernel is a sum of exponentials, the GRLE is equivalent to a Markovian system with added variables. We establish the…

Probability · Mathematics 2026-03-17 Ethan Baker , Manh Hong Duong , Hung Dang Nguyen

The complexity of molecular dynamics simulations necessitates dimension reduction and coarse-graining techniques to enable tractable computation. The generalized Langevin equation (GLE) describes coarse-grained dynamics in reduced…

Computational Physics · Physics 2020-06-08 Francesca Grogan , Huan Lei , Xiantao Li , Nathan A. Baker

Wang et al. [PNAS 106 (2009) 15160] have found that in several systems the linear time dependence of the mean-square displacement (MSD) of diffusing colloidal particles, typical of normal diffusion, is accompanied by a non-Gaussian…

Statistical Mechanics · Physics 2015-06-19 Mykyta V. Chubynsky , Gary W. Slater

The stochastic motion in a nonhomogeneous medium with traps is studied and diffusion properties of that system are discussed. The particle is subjected to a stochastic stimulation obeying a general L\'evy stable statistics and experiences…

Statistical Mechanics · Physics 2015-06-11 Tomasz Srokowski

The dynamics of unimolecular photo-triggered reactions can be strongly affected by the surrounding medium. An accurate description of these reactions requires knowing the free energy surface (FES) and the friction felt by the reactants.…

It is shown that the solution of generalized Langevin equation can be obtained on the basis of simple comparison of the time scale for the velocity autocorrelation function of a particle (atom, molecule) and of the time scale for the…

Statistical Mechanics · Physics 2017-02-28 Anatolii V. Mokshin , Bulat N. Galimzyanov

In this work, the motion of a dust particle under the influence of the random force due to dust charge fluctuations is considered as a non-Markovian stochastic process. Memory effects in the velocity process of the dust particle are…

Plasma Physics · Physics 2017-10-26 Zahra Ghannad , Hossein Hakimi Pajouh

A simple manner to describe the diffusive relaxation of a colloidal fluid adsorbed in a porous medium is to model the porous medium as a set of spherical particles fixed in space at random positions with prescribed statistical structural…

The Generalized Langevin Equation, in history, arises as a natural fix for the rather traditional Langevin equation when the random force is no longer memoryless. It has been proved that with fractional Gaussian noise (fGn) mostly…

Numerical Analysis · Mathematics 2022-09-20 Di Fang , Lei Li

The problem of biological motion is a very intriguing and topical issue. Many efforts are being focused on the development of novel modeling approaches for the description of anomalous diffusion in biological systems, such as the very…

The transport equation of active motion is generalised to consider time-fractional dynamics for describing the anomalous diffusion of self-propelled particles observed in many different systems. In the present study, we consider an…

Statistical Mechanics · Physics 2023-10-27 Francisco J. Sevilla , Guillermo Chacón-Acosta , Trifce Sandev

In convection-dominated flows, robustness of the spatial discretisation is a key property. While Interior Penalty Galerkin (IPG) methods already proved efficient in the situation of large mesh Peclet numbers, Arbitrary Lagrangian-Eulerian…

Numerical Analysis · Mathematics 2025-04-16 Ezra Rozier , Jörn Behrens

It has been become standard practice to describe steady-state non-equilibrium phenomena by Langevin equations with colored noise and time-dependent friction kernels that do not obey the fluctuation-dissipation theorem, but since these…

Statistical Mechanics · Physics 2023-10-03 Roland R. Netz

The mean-square displacement (MSD) is widely utilized to study the dynamical properties of stochastic processes. The time-averaged MSD (TAMSD) provides some information on the dynamics which cannot be extracted from the ensemble-averaged…

Statistical Mechanics · Physics 2015-10-07 Takashi Uneyama , Tomoshige Miyaguchi , Takuma Akimoto

We present a statistical mechanics framework for modeling equilibrium friction coefficients using the Generalized Langevin Equation (GLE). We show that the kernel, obtained via the Fluctuation-Dissipation Theorem (FDT) from the stochastic…

Plasma Physics · Physics 2026-05-01 N. R. Sree Harsha , Zhenyuan Yu , Chuang Ren , Virginia Billings , Michael Huang

The transport of individual particles in inhomogeneous environments is complex and exhibits non-Markovian responses. The latter may be quantified by a memory function within the framework of the linear generalised Langevin equation (GLE).…

Soft Condensed Matter · Physics 2024-07-08 Arthur V. Straube , Felix Höfling

In classical diffusion, particle step-sizes have a Gaussian distribution. However, in superdiffusion, they have power-law tails, with transport dominated by rare, long L\'evy flights. Similarly, if the time interval between scattering…

High Energy Astrophysical Phenomena · Physics 2025-10-08 Naixin Liang , Siang Peng Oh

Starting from a generalized elastic model which accounts for the stochastic motion of several physical systems such as membranes, (semi)flexible polymers and fluctuating interfaces among others, we derive the fractional Langevin equation…

Statistical Mechanics · Physics 2012-03-16 Alessandro Taloni , Aleksei Chechkin , Joseph Klafter

We analyze prediction error in stochastic dynamical systems with memory, focusing on generalized Langevin equations (GLEs) formulated as stochastic Volterra equations. We establish that, under a strongly convex potential, trajectory…

Machine Learning · Statistics 2025-12-12 Quanjun Lang , Jianfeng Lu

Anomalous diffusion occurs in many physical and biological phenomena, when the growth of the mean squared displacement (MSD) with time has an exponent different from one. We show that recurrent neural networks (RNN) can efficiently…

Statistical Mechanics · Physics 2019-07-24 Stefano Bo , Falko Schmidt , Ralf Eichhorn , Giovanni Volpe