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This paper considers the reduction of the Langevin equation arising from bio-molecular models. To facilitate the construction and implementation of the reduced models, the problem is formulated as a reduced-order modeling problem. The…

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

We will construct a theory which can explain the dynamics toward the steady state self-gravitating systems (SGSs) where many particles interact via the gravitational force. Real examples of SGS in the universe are globular clusters and…

Cosmology and Nongalactic Astrophysics · Physics 2011-08-09 Tohru Tashiro , Takayuki Tatekawa

By exact projection in phase space we derive the generalized Langevin equation (GLE) for time-filtered observables. We employ a general convolution filter that directly acts on arbitrary phase-space observables and can involve low-pass,…

Statistical Mechanics · Physics 2024-09-20 Roland R. Netz

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

Necessary and sufficient conditions are presented for the existence of (second order) stationary solutions of the generalized Langevin equation under appropriate assumptions on the associated memory kernel. When this stochastic equation is…

Mathematical Physics · Physics 2025-07-24 Martin Hanke

Langevin simulation provides an effective way to study collisional effects in beams by reducing the six-dimensional Fokker-Planck equation to a group of stochastic ordinary differential equations. These resulting equations usually have…

Accelerator Physics · Physics 2007-05-23 Ji Qiang , Salman Habib

We systematically derive the quantum generalized nonlinear Langevin equation using Morozov's projection operator method. This approach extends the linear Mori-Zwanzig projection operator technique, allowing for the inclusion of nonlinear…

Statistical Mechanics · Physics 2024-09-23 Jin Hu

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

The focus of our study in this paper is on the active dynamics and a fractional generalized Langevin equation with a memory kernel K(t). The Fokker-Planck equation is obtained by deriving it from a second-order differential equation. The…

Statistical Mechanics · Physics 2024-12-17 Yun Jeong Kang , Kyungsik Kim

We introduce a machine learning-based approach called ab initio generalized Langevin equation (AIGLE) to model the dynamics of slow collective variables in materials and molecules. In this scheme, the parameters are learned from atomistic…

Computational Physics · Physics 2024-04-02 Pinchen Xie , Roberto Car , Weinan E

This work presents a systematic methodology for describing the transient dynamics of coarse-grained molecular systems inferred from all-atom simulated data. We suggest Langevin-type dynamics where the coarse-grained interaction potential…

Numerical Analysis · Mathematics 2023-09-22 G. Baxevani , V. Harmandaris , E. Kalligiannaki , I. Tsantili

The concept of stochastic Lagrangian and its use in statistical dynamics is illustrated theoretically, and with some examples. Dynamical variables undergoing stochastic differential equations are stochastic processes themselves, and their…

Statistical Mechanics · Physics 2020-03-18 Massimo Materassi

We describe a stochastic, dynamical system capable of inference and learning in a probabilistic latent variable model. The most challenging problem in such models - sampling the posterior distribution over latent variables - is proposed to…

Machine Learning · Statistics 2022-07-26 Michael Y. -S. Fang , Mayur Mudigonda , Ryan Zarcone , Amir Khosrowshahi , Bruno A. Olshausen

Reconstruction of equations of motion from incomplete or noisy data and dimension reduction are two fundamental problems in the study of dynamical systems with many degrees of freedom. For the latter extensive efforts have been made but…

Statistical Mechanics · Physics 2011-02-08 Jianhua Xing , Kenneth S Kim

Many complex systems operating far from the equilibrium exhibit stochastic dynamics that can be described by a Langevin equation. Inferring Langevin equations from data can reveal how transient dynamics of such systems give rise to their…

Machine Learning · Statistics 2021-11-01 Mikhail Genkin , Owen Hughes , Tatiana A. Engel

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

We obtain the memory kernel of the generalized Langevin equation, describing a particle interacting with longitudinal phonons in a liquid. The kernel is obtained analytically at T=0 Kelvin and numerically at T>0 Kelvin. We find that it…

Statistical Mechanics · Physics 2009-10-31 Gady Frenkel , Moshe Schwartz

We show that the coarse-grained dynamics model with the time-dependent and fluctuating potential (transient potential) can be derived from the microscopic Hamiltonian dynamics. The concept of the transient potential was first introduced…

Soft Condensed Matter · Physics 2022-04-18 Takashi Uneyama

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

In this paper, we consider the generalised (higher order) Langevin equation for the purpose of simulated annealing and optimisation of nonconvex functions. Our approach modifies the underdamped Langevin equation by replacing the Brownian…

Probability · Mathematics 2023-11-01 Martin Chak , Nikolas Kantas , Grigorios A. Pavliotis