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We present a data-driven approach to determine the memory kernel and random noise in generalized Langevin equations. To facilitate practical implementations, we parameterize the kernel function in the Laplace domain by a rational function,…

Computational Physics · Physics 2022-06-08 Huan Lei , Nathan Baker , Xiantao Li

We discuss general multi-dimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety…

Statistical Mechanics · Physics 2015-04-14 Miguel Vera Moreno , Zochil González Arenas , Daniel G. Barci

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

Generalized Langevin equations with non-linear forces and position-dependent linear friction memory kernels, such as commonly used to describe the effective dynamics of coarse-grained variables in molecular dynamics, are rigorously derived…

Statistical Mechanics · Physics 2022-07-07 Hadrien Vroylandt , Pierre Monmarché

We present a derivation of a coarse-grained model from the Langevin dynamics. The focus is placed on the memory kernel function and the fluctuation-dissipation theorem. Also presented is an hierarchy of approximations for the memory and…

Numerical Analysis · Mathematics 2019-10-04 Lina Ma , Xiantao Li , Chun Liu

We present a comprehensive study of the symmetries of the generating functionals of generic Langevin processes with multiplicative colored noise. We treat both Martin-Siggia-Rose-Janssen-deDominicis and supersymmetric formalisms. We…

Statistical Mechanics · Physics 2010-11-24 Camille Aron , Giulio Biroli , Leticia F. Cugliandolo

The underdamped, non-linear, generalized Langevin equation is widely used to model coarse-grained dynamics of soft and biological materials. By means of a projection operator formalism, we show under which approximations this equation can…

Soft Condensed Matter · Physics 2022-02-04 Fabian Glatzel , Tanja Schilling

A random multiplicative process with additive noise is described by a Langevin equation. We show that the fluctuation-dissipation relation is satisfied in the Langevin model, if the noise strength is not so strong.

Statistical Mechanics · Physics 2009-11-07 H. Sakaguchi

We present a numerical method to compute the approximation of the memory functions in the generalized Langevin models for collective dynamics of macromolecules. We first derive the exact expressions of the memory functions, obtained from…

Numerical Analysis · Mathematics 2015-06-19 Minxin Chen , Xiantao Li , Chun Liu

We present the reduction of generalized Langevin equations to a coordinate-only stochastic model, which in its exact form, involves a forcing term with memory and a general Gaussian noise. It will be shown that a similar…

Numerical Analysis · Mathematics 2019-10-04 Lina Ma , Xiantao Li , Chun Liu

The kangaroo process (KP) is characterized by various forms of the covariance and can serve as a useful model of random noises. We discuss properties of that process for the exponential, stretched exponential and algebraic (power-law)…

Statistical Mechanics · Physics 2009-11-07 T. Srokowski

We consider the asymptotic behaviour of the fluctuation process for large stochastic systems of interacting particles driven by both idiosyncratic and common noise with an interaction kernel \(k \in L^2(\R^d) \cap L^\infty(\R^d)\). Our…

Probability · Mathematics 2026-05-28 Paul Nikolaev

When a probe particle immersed in a fluid with nonlinear interactions is subject to strong driving, the cumulants of the stochastic force acting on the probe are nonlinear functionals of the driving protocol. We present a Volterra series…

Statistical Mechanics · Physics 2024-12-17 Juliana Caspers , Matthias Krüger

Various approaches to stochastic processes exist, noting that key properties such as measurability and continuity are not trivially satisfied. We introduce a new theory for Gaussian processes using improper linear functionals. Using a…

Statistics Theory · Mathematics 2020-10-15 Niels Lundtorp Olsen

We study the generalized Langevin equation approach to anomalous diffusion for a harmonic oscillator and a free particle driven by different forms of internal noises, such as power-law-correlated and distributed-order noises that fulfil…

Statistical Mechanics · Physics 2023-09-01 Z. Tomovski , K. Gorska , T. Pietrzak , R. Metzler , T. Sandev

Functionals of particles' paths have diverse applications in physics, mathematics, hydrology, economics, and other fields. Under the framework of continuous time random walk (CTRW), the governing equations for the probability density…

Statistical Mechanics · Physics 2018-11-21 Xudong Wang , Yao Chen , Weihua Deng

The generalized Langevin equation describes anomalous dynamics. Noise is not only the origin of uncertainty but also plays a positive role in helping to detect signal with information, termed stochastic resonance (SR). This paper analyzes…

Statistical Mechanics · Physics 2018-04-10 Yao Chen , Xudong Wang , Weihua Deng

Fluctuation theorems based on time-reversal have provided remarkable insight into the non-equilibrium statistics of thermodynamic quantities like heat, work, and entropy production. These types of laws impose constraints on the…

Statistical Mechanics · Physics 2022-11-30 Max Innerbichler , Andrei Militaru , Martin Frimmer , Lukas Novotny , Christoph Dellago

We present a simple derivation of the stochastic equation obeyed by the density function for a system of Langevin processes interacting via a pairwise potential. The resulting equation is considerably different from the phenomenological…

Condensed Matter · Physics 2009-10-28 David S. Dean

A new approach for the analysis of Langevin-type stochastic processes in the presence of strong measurement noise is presented. For the case of Gaussian distributed, exponentially correlated, measurement noise it is possible to extract the…

Data Analysis, Statistics and Probability · Physics 2013-05-29 Bernd Lehle
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