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Related papers: Effective Action Method for Langevin Equation

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Generalizing response theory of open systems far from equilibrium is a central quest of nonequilibrium statistical physics. Using stochastic thermodynamics, we develop an algebraic method to study the response of nonequilibrium steady state…

Statistical Mechanics · Physics 2023-08-09 Timur Aslyamov , Massimiliano Esposito

Non-perturbative formulations of field theories are essential to capture intriguing physical phenomena, including confinement in QCD, spontaneous supersymmetry breaking, and dynamical compactification in superstrings. Lattice regularization…

High Energy Physics - Lattice · Physics 2023-09-08 Arpith Kumar

We present a general and model-independent method to obtain an effective Markovian quantum kinetic equation for the expectation value of a slowly evolving scalar field in an adiabatically evolving background from first principles of…

High Energy Physics - Phenomenology · Physics 2022-05-25 Gilles Buldgen , Marco Drewes , Jin U Kang , Ui Ri Mun

We use the semi-discrete method, originally proposed in Halidias (2012), Semi-discrete approximations for stochastic differential equations and applications, International Journal of Computer Mathematics, 89(6), to reproduce qualitative…

Numerical Analysis · Mathematics 2017-08-29 Ioannis S. Stamatiou

A large class of quantum and statistical field theoretical models, encompassing relevant condensed matter and non-abelian gauge systems, are defined in terms of complex actions. As the ordinary Monte-Carlo methods are useless in dealing…

Statistical Mechanics · Physics 2009-11-11 L. Moriconi , M. Moriconi

In applied sciences, we often deal with deterministic simulation models that are too slow for simulation-intensive tasks such as calibration or real-time control. In this paper, an emulator for a generic dynamic model, given by a system of…

Methodology · Statistics 2012-07-06 Carlo Albert

The dynamics of weakly coupled, non-abelian gauge fields at high temperature is non-perturbative if the characteristic momentum scale is of order |k|~ g^2 T. Such a situation is typical for the processes of electroweak baryon number…

High Energy Physics - Phenomenology · Physics 2009-09-28 Claus Zahlten , Andres Hernandez , Michael G. Schmidt

Many complex systems are characterized by intriguing spatio-temporal structures. Their mathematical description relies on the analysis of appropriate correlation functions. Functional integral techniques provide a unifying formalism that…

Statistical Mechanics · Physics 2009-11-12 Uwe C. Tauber

Both linear and nonlinear Langevin equations are derived directly from the Liouville equation for an exactly solvable model consisting of a Brownian particle of mass $M$ interacting with ideal gas molecules of mass $m$ via a quadratic…

Statistical Mechanics · Physics 2009-11-10 Alexander V. Plyukhin , Jeremy Schofield

Automatic machine learning of empirical models from experimental data has recently become possible as a result of increased availability of computational power and dedicated algorithms. Despite the successes of non-parametric inference and…

Statistical Mechanics · Physics 2024-06-04 Yunfei Huang , Youssef Mabrouk , Gerhard Gompper , Benedikt Sabass

We recently showed that the dynamics of coarse-grained observables in systems out of thermal equilibrium are governed by the non-stationary generalized Langevin equation [J. Chem. Phys. 147, 214110 (2017), J. Chem. Phys. 150, 174118…

Statistical Mechanics · Physics 2021-05-21 Fabian Glatzel , Tanja Schilling

We investigate in this work the validity of linear stochastic models for nonlinear dynamical systems. We exploit as our basic tool a previously proposed Rayleigh-Ritz approximation for the effective action of nonlinear dynamical systems…

chao-dyn · Physics 2009-10-31 Gregory L. Eyink

We propose a new method called the N-particle underdamped Langevin algorithm for optimizing a special class of non-linear functionals defined over the space of probability measures. Examples of problems with this formulation include…

Computation · Statistics 2024-02-07 Qiang Fu , Ashia Wilson

Analogue to the well-known Langevin Monte Carlo method, in this article we provide a method to sample from a target distribution \(\pi\) by simulating a solution of a stochastic differential equation. Hereby, the stochastic differential…

Probability · Mathematics 2023-03-15 David Oechsler

A linear open quantum system consisting of a harmonic oscillator linearly coupled to an infinite set of independent harmonic oscillators is considered; these oscillators have a general spectral density function and are initially in a…

Quantum Physics · Physics 2009-11-06 Esteban Calzetta , Albert Roura , Enric Verdaguer

We investigate a stochastic approach to non-equilibrium quantum spin systems based on recent insights linking quantum and classical dynamics. Exploiting a sequence of exact transformations, quantum expectation values can be recast as…

Statistical Mechanics · Physics 2019-01-31 S. De Nicola , B. Doyon , M. J. Bhaseen

The non-Markovian dynamics of open quantum systems is still a challenging task, particularly in the non-perturbative regime at low temperatures. While the Stochastic Liouville-von Neumann equation (SLN) provides a formally exact tool to…

Statistical Mechanics · Physics 2016-12-21 Michael Wiedmann , Jürgen T. Stockburger , Joachim Ankerhold

Given a discrete stochastic process, for example a chemical reaction system or a birth and death process, we often want to find a continuous stochastic approximation so that the techniques of stochastic differential equations may be brought…

Statistical Mechanics · Physics 2010-09-29 Edward W. J. Wallace

By combining the two-particle-irreducible (2PI) effective action common in non-equilibrium quantum field theory with the classical Martin-Siggia-Rose formalism, self-consistent equations of motion for the first and second cumulants of…

Disordered Systems and Neural Networks · Physics 2022-05-31 Tim Bode

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
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