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Using a shortcut way we have derived the Fokker-Planck equation for the Langevin dynamics with a generalized frictional memory kernel and time-dependent force field. Then we have shown that this method is applicable for the non-Markovian…

Statistical Mechanics · Physics 2022-12-01 Joydip Das , Mousumi Biswas , Bidhan Chandra Bag

We discuss the stochastic process of creation and annihilation of particles, i.e., the $A^{n} \rightleftarrows B$ process in which $n$ particles $A$s and one particle $B$ are transformed to each other. Considering the case that the…

Statistical Mechanics · Physics 2024-04-23 Shigehiro Yasui , Yutaka Hatakeyama , Yoshiyasu Okuhara

In this paper, we focus on the control of the mean field equilibrium of non linear networks of the Langevin type in the limit of small noise. Using iterative linear approximations, we derive a formula that prescribes a control strategy in…

Statistical Mechanics · Physics 2017-07-06 Giuseppe Forte , Dervis C. Vural

Generalized Langevin equations (GLEs) can be systematically derived via dimensional reduction from high-dimensional microscopic systems. For linear models the derivation can either be based on projection operator techniques such as the…

Statistical Mechanics · Physics 2022-03-30 Gerhard Jung

The time evolution problem for non-self adjoint second order differential operators is studied by means of the path integral formulation. Explicit computation of the path integral via the use of certain underlying stochastic differential…

Mathematical Physics · Physics 2021-07-20 Anastasia Doikou , Simon J. A. Malham , Anke Wiese

We develop a systematic approach to the linear-noise approximation for stochastic reaction systems with distributed delays. Unlike most existing work our formalism does not rely on a master equation, instead it is based upon a dynamical…

Statistical Mechanics · Physics 2013-12-13 Tobias Brett , Tobias Galla

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 introduce a new method to accurately and efficiently estimate the effective dynamics of collective variables in molecular simulations. Such reduced dynamics play an essential role in the study of a broad class of processes, ranging from…

Statistical Mechanics · Physics 2022-03-28 Hadrien Vroylandt , Ludovic Goudenège , Pierre Monmarché , Fabio Pietrucci , Benjamin Rotenberg

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

A nonequilibrium fluctuation theorem is established for a colloidal particle driven by an external force within the hydrodynamic theory of Brownian motion, describing hydrodynamic memory effects such as the t^(-3/2) power-law decay of the…

Statistical Mechanics · Physics 2020-06-24 Pierre Gaspard

The stochastic dynamics of a rigid inclusion constrained to move on a curved surface has many applications in biological and soft matter physics, ranging from the diffusion of passive or active membrane proteins to the motion of phoretic…

Soft Condensed Matter · Physics 2025-04-18 Balázs Németh , Ronojoy Adhikari

We model non-stationary volume-price distributions with a log-normal distribution and collect the time series of its two parameters. The time series of the two parameters are shown to be stationary and Markov-like and consequently can be…

Statistical Finance · Quantitative Finance 2017-05-04 Joana Estevens , Paulo Rocha , Joao Boto , Pedro Lind

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 generalize Lyons' rough paths theory in order to give a pathwise meaning to some nonlinear infinite-dimensional evolution equation associated to an analytic semigroup and driven by an irregular noise. As an illustration, we discuss a…

Probability · Mathematics 2010-01-26 Massimiliano Gubinelli , Samy Tindel

Stochastic reduced-order models are widely used to represent the effective dynamics of complex systems, but estimating their drift and diffusion coefficients from data remains challenging. Standard approaches often rely on short-time…

Machine Learning · Statistics 2026-04-28 Ludovico T. Giorgini

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

The generation of non-separable, physically motivated covariance functions is a theme of ongoing research interest, given that only a few classes of such functions are available. We construct a non-separable space-time covariance function…

Methodology · Statistics 2016-12-20 Dionissios T. Hristopulos , Ivi C. Tsantili

Previous years researchers began to simulate open quantum system, taking into account the interaction between system and the environment. One approach to deal with this problem is to use the density matrix within the Liouville-von-Neumann…

Quantum Physics · Physics 2025-09-15 Mohammad Attrash , Roi Baer

Formulated is a new systematic method for obtaining higher order corrections in numerical simulation of stochastic differential equations (SDEs), i.e., Langevin equations. Random walk step algorithms within a given order of finite $\Delta…

High Energy Physics - Lattice · Physics 2009-10-28 H. Nakajima , S. Furui

In this paper, we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular dynamics. The latter are ubiquitous in physicochemical and biological…

Numerical Analysis · Mathematics 2016-04-20 Vagelis Harmandaris , Evangelia Kalligiannaki , Markos A. Katsoulakis , Petr Plecháč