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The diffusion equation is the primary tool to study the movement dynamics of a free Brownian particle, but when spatial heterogeneities in the form of permeable interfaces are present, no fundamental equation has been derived. Here we…

Statistical Mechanics · Physics 2022-09-14 Toby Kay , Luca Giuggioli

We investigate evolution equations for anomalous diffusion employing fractional derivatives in space and time. Linkage between the space-time variables leads to a new type of fractional derivative operator. Fractional diffusion equations…

Mathematical Physics · Physics 2007-05-23 Andrzej J. Turski , Barbara Atamaniuk , Ewa Turska

The purpose of this paper is to examine the Lagrangian stochastic modeling of the fluid velocity seen by inertial particles in a nonhomogeneous turbulent flow. A new Langevin-type model, compatible with the transport equation of the drift…

Fluid Dynamics · Physics 2009-07-01 Boris Arcen , Anne Tanière

We investigate the fluctuation dynamics of a probe around a deterministic motion induced by interactions with driven particles. The latter constitute the nonequilibrium medium in which the probe is immersed and is modelled as overdamped…

Statistical Mechanics · Physics 2017-01-03 Christian Maes , Stefano Steffenoni

In this work, we are interested in building the fully discrete scheme for stochastic fractional diffusion equation driven by fractional Brownian sheet which is temporally and spatially fractional with Hurst parameters $H_{1}, H_{2}…

Numerical Analysis · Mathematics 2022-01-27 Daxin Nie , Jing Sun , Weihua Deng

Porous materials are widely used for applications in gas storage and separation. The diffusive properties of a variety of gases in porous media can be modeled using molecular dynamics simulations that can be computationally demanding…

Chemical Physics · Physics 2023-09-19 Gastón González , Rubén A. Fritz , Yamil J. Colón , Felipe Herrera

We have revisited the Brownian motion on the basis of the fractional Langevin equation which turns out to be a particular case of the generalized Langevin equation introduced by Kubo on 1966. The importance of our approach is to model the…

Mathematical Physics · Physics 2008-06-06 Francesco Mainardi , Paolo Pironi

We review recent developments of slow/fast stochastic differential equations, and also present a new result on Diffusion Homogenisation Theory with fractional and non-strong-mixing noise and providing new examples. The emphasise of the…

Probability · Mathematics 2023-03-07 Johann Gehringer , Xue-Mei Li

The Fractional Langevin Equation (FLE) describes a non-Markovian Generalized Brownian Motion with long time persistence (superdiffusion), or anti-persistence (subdiffusion) of both velocity-velocity correlations, and position increments. It…

Statistical Mechanics · Physics 2011-07-11 P. Siegle , I. Goychuk , P. Hanggi

Diffusion models are powerful tools for sampling from high-dimensional distributions by progressively transforming pure noise into structured data through a denoising process. When equipped with a guidance mechanism, these models can also…

Machine Learning · Computer Science 2026-05-04 Saeed Mohseni-Sehdeh , Walid Saad , Kei Sakaguchi , Tao Yu

Fractional kinetic equations employ non-integer calculus to model anomalous relaxation and diffusion in many systems. While this approach is well explored, it so far failed to describe an important class of transport in disordered systems.…

Statistical Mechanics · Physics 2021-01-04 Wanli Wang , Eli Barkai

We give an exact solution to the generalized Langevin equation of motion of a charged Brownian particle in a uniform magnetic field that is driven internally by an exponentially-correlated stochastic force. A strong dissipation regime is…

Statistical Mechanics · Physics 2008-02-13 Francis N. C. Paraan , Mikhail P. Solon , J. P. Esguerra

We present here a conjecture about the equivalence between the noise density of states of a system governed by a generalized Langevin equation and the fluctuation in the energy density of states in a Hamiltonian system. We present evidence…

Disordered Systems and Neural Networks · Physics 2007-05-23 Mendeli H. Vainstein , Rafael Morgado , Fernando A. Oliveira

In this paper we introduce a novel method to simulate lateral diffusion of inclusions in a fluctuating membrane. The regarded systems are governed by two dynamic processes: the height fluctuations of the membrane and the diffusion of the…

Soft Condensed Matter · Physics 2007-05-23 Ellen Reister-Gottfried , Stefan M. Leitenberger , Udo Seifert

Diffusion studies of adsorbates moving on a surface are often analyzed using 2D Langevin simulations. These simulations are computationally cheap and offer valuable insight into the dynamics, however, they simplify the complex interactions…

Materials Science · Physics 2015-05-28 Moshe Diamant , Saar Rahav , Riccardo Ferrando , Gil Alexandrowicz

Theories with a sign problem due to a complex action or Boltzmann weight can sometimes be numerically solved using a stochastic process in the complexified configuration space. However, the probability distribution effectively sampled by…

High Energy Physics - Lattice · Physics 2025-10-06 Gert Aarts , Diaa E. Habibi , Lingxiao Wang , Kai Zhou

The role of external forces in systems exhibiting anomalous diffusion is discussed on the basis of the describing Langevin equations. Since there exist different possibilities to include the effect of an external field the concept of {\it…

Statistical Mechanics · Physics 2015-05-13 S. Eule , R. Friedrich

We study the Langevin dynamics of diffusive particles with regular pairwise interactions under mean-field scaling. By approximating empirical distributions with conditional distributions, we establish coercive and contractive properties for…

Probability · Mathematics 2026-05-28 Songbo Wang

We present a numerical scheme for simulating the dynamics of Brownian particles suspended in a fluid. The motion of the particles is tracked by the Langevin equation, whereas the host fluid flow is analyzed by using the lattice Boltzmann…

Mesoscale and Nanoscale Physics · Physics 2019-10-30 Hiroaki Yoshida , Tomoyuki Kinjo , Hitoshi Washizu

We focus on variational inference in dynamical systems where the discrete time transition function (or evolution rule) is modelled by a Gaussian process. The dominant approach so far has been to use a factorised posterior distribution,…

Machine Learning · Statistics 2018-12-17 Alessandro Davide Ialongo , Mark van der Wilk , James Hensman , Carl Edward Rasmussen