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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

We extend the generalized Langevin model, originally developed for the Lagrangian fluid particle velocity in constant-density shear-driven turbulence, to variable-density (VD) pressure-gradient-driven flows. VD effects due to non-uniform…

Fluid Dynamics · Physics 2015-05-27 J. Bakosi , J. R. Ristorcelli

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

Understanding how nonequilibrium systems respond to perturbations is a central challenge in physics. In this work, we establish mutual linearity in nonequilibrium overdamped Langevin systems. This theory provides a framework for controlling…

Statistical Mechanics · Physics 2026-05-11 Jiming Zheng , Zhiyue Lu

In this paper we provide an extension for the method of Discrete Lagrangian Descriptors with the purpose of exploring the phase space of unbounded maps. The key idea is to construct a working definition, that builds on the original approach…

Chaotic Dynamics · Physics 2020-05-20 Víctor J. García-Garrido

We consider linear dynamical systems with a structure of a multigraph. The vertices are associated to linear spaces and the edges correspond to linear maps between those spaces. We analyse the asymptotic growth of trajectories (associated…

Dynamical Systems · Mathematics 2016-07-05 Antonio Cicone , Nicola Guglielmi , Vladimir Protasov

We present a new variational principle for the gyrokinetic system, similar to the Maxwell-Vlasov action presented in Ref. 1. The variational principle is in the Eulerian frame and based on constrained variations of the phase space fluid…

Plasma Physics · Physics 2013-02-15 J. Squire , H. Qin , W. M. Tang , C. Chandre

A key task in Bayesian machine learning is sampling from distributions that are only specified up to a partition function (i.e., constant of proportionality). One prevalent example of this is sampling posteriors in parametric distributions,…

Machine Learning · Computer Science 2020-09-10 Rong Ge , Holden Lee , Andrej Risteski

Overdamped Langevin dynamics are reversible stochastic differential equations which are commonly used to sample probability measures in high-dimensional spaces, such as the ones appearing in computational statistical physics and Bayesian…

Numerical Analysis · Mathematics 2025-02-10 Tony Lelièvre , Grigorios A. Pavliotis , Geneviève Robin , Régis Santet , Gabriel Stoltz

In this study we consider the Hamiltonian approach for the construction of a map for a system with nonlinear resonant interaction, including phase trapping and phase bunching effects. We derive basic equations for a single resonant…

Recent work has addressed the problem of inferring Langevin dynamics from data. In this work, we address the problem of relating terms in the Langevin equation to statistical properties, such as moments of the probability density function…

Statistical Mechanics · Physics 2026-04-09 Yeeren I. Low

The usual Langevin approach to describe systems driven by noise fails to describe the long time behavior of systems with multiple attractors. The solution of the associated linear Fokker-Planck equation is always unique, even though it…

Statistical Mechanics · Physics 2017-06-20 M. Morillo , J. M. Casado

This paper deals with the analysis of stochastic systems which can be described by a Langevin equation. By the method presented in this paper drift and diffusion terms of the corresponding Fokker-Planck equation can be extracted from the…

Condensed Matter · Physics 2009-10-31 S. Siegert , R. Friedrich , J. Peinke

We describe a simple stochastic method, so-called Langevin approach, which enables one to extract evolution equations of stochastic variables from a set of measurements. Our method is parameter-free and it is based on the nonlinear Langevin…

Data Analysis, Statistics and Probability · Physics 2015-02-19 Nico Reinke , André Fuchs , Wided Medjroubi , Pedro G. Lind , Matthias Wächter , Joachim Peinke

We investigate the continuum limit that the number of beads goes to infinity in the ring polymer representation of thermal averages. Studying the continuum limit of the trajectory sampling equation sheds light on possible preconditioning…

Chemical Physics · Physics 2020-02-06 Jianfeng Lu , Yulong Lu , Zhennan Zhou

In this paper, we study the problem of sampling from distributions of the form p(x) \propto e^{-\beta f(x)} for some function f whose values and gradients we can query. This mode of access to f is natural in the scenarios in which such…

Probability · Mathematics 2020-09-22 Ankur Moitra , Andrej Risteski

Considering Langevin dynamics we derive the general form of the stochastic differential that satisfies the Gallavotti-Cohen symmetry. This extends the work previously done by Kurchan, and Lebowitz and Spohn on such systems, and we treat…

Statistical Mechanics · Physics 2007-05-23 Martin Depken

In this paper we consider the dynamics of harmonically-confined atomic gases. We present various general results which are independent of particle statistics, interatomic interactions and dimensionality. Of particular interest is the…

Quantum Gases · Physics 2014-03-13 Z. Wu , E. Zaremba

Diffusion in heterogeneous energy and diffusivity landscapes is widespread in biological systems. However, solving the Langevin equation in such environments introduces ambiguity due to the interpretation parameter $\alpha$, which depends…

Statistical Mechanics · Physics 2025-05-20 Adrian Pacheco-Pozo , Igor M. Sokolov , Ralf Metzler , Diego Krapf

D. B. Br\"{u}ckner et al. [Phys. Rev. Lett. 125, 058103 (2020)] have described a novel method for inferring the dynamics of systems governed by an underdamped Langevin equation in the presence of measurement noise. While this is a…

Statistical Mechanics · Physics 2026-04-10 Yeeren I. Low