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In this paper we present a formulation of the nonlinear stochastic differential equation which allows for systematic approximations. The method is not restricted to the asymptotic, i.e., stationary, regime but can be applied to derive…

chao-dyn · Physics 2009-10-22 A. Crisanti , U. Marini Bettolo Marconi

We consider Lagrangian systems in the limit of infinitely many particles. It is shown that the corresponding discrete action functionals Gamma-converge to a continuum action functional acting on probability measures of particle…

Numerical Analysis · Mathematics 2013-01-16 Bernd Schmidt

We consider the one-dimensional Glauber dynamics with coupling disorder in terms of bilinear fermion Hamiltonians. Dynamic exponents embodied in the spectrum gap of these latter are evaluated numerically by averaging over both binary and…

Statistical Mechanics · Physics 2013-06-06 Marcelo D. Grynberg , Robin B. Stinchcombe

We discuss the two-dimensional motion of a Brownian particle that is confined to a harmonic trap and driven by a shear flow. The surrounding medium induces memory effects modelled by a linear, typically nonreciprocal coupling of the…

Statistical Mechanics · Physics 2024-04-26 Lea Fernandez , Siegfried Hess , Sabine H. L. Klapp

The reduction of high-dimensional systems to effective models on a smaller set of variables is an essential task in many areas of science. For stochastic dynamics governed by diffusion processes, a general procedure to find effective…

Dynamical Systems · Mathematics 2020-12-15 Feliks Nüske , Péter Koltai , Lorenzo Boninsegna , Cecilia Clementi

This paper is devoted to the study of acceleration methods for an inequality constrained convex optimization problem by using Lyapunov functions. We first approximate such a problem as an unconstrained optimization problem by employing the…

Optimization and Control · Mathematics 2024-11-25 Juan Liu , Nan-Jing Huang , Xian-Jun Long , Xue-song Li

We consider non-linear evolution equations arising from mean-field limits of particle systems on discrete spaces. We investigate a notion of curvature bounds for these dynamics based on convexity of the free energy along interpolations in a…

Probability · Mathematics 2020-06-04 Matthias Erbar , Max Fathi , André Schlichting

We summarize recent results regarding the equilibrium and non-equilibrium behavior of cold dilute atomic gases in the limit in which the two body scattering length a goes to infinity. In this limit the system is described by a Galilean…

Nuclear Theory · Physics 2017-08-23 Thomas Schaefer

We present in detail a Langevin formalism for constructing stochastic dynamical equations for active-matter systems coupled to a thermal bath. We apply the formalism to clarify issues of principle regarding the sources and signatures of…

Soft Condensed Matter · Physics 2018-12-26 Lokrshi Prawar Dadhichi , Ananyo Maitra , Sriram Ramaswamy

In previous work, we introduced a method for determining convergence rates for integration methods for the kinetic Langevin equation for $M$-$\nabla$Lipschitz $m$-log-concave densities [arXiv:2302.10684, 2023]. In this article, we exploit…

Numerical Analysis · Mathematics 2023-06-16 Benedict Leimkuhler , Daniel Paulin , Peter A. Whalley

In this paper, we investigate the exponential ergodicity in a Wasserstein-type distance for a damping Hamiltonian dynamics with state-dependent and non-local collisions, which indeed is a special case of piecewise deterministic Markov…

Probability · Mathematics 2022-04-05 Jianhai Bao , Jian Wang

We consider the problem of equilibration of a single oscillator system with dynamics given by the generalized Langevin equation. It is well-known that this dynamics can be obtained if one considers a model where the single oscillator is…

Statistical Mechanics · Physics 2009-11-11 Abhishek Dhar , Kshitij Wagh

Understanding neural dynamics is a central topic in machine learning, non-linear physics and neuroscience. However, the dynamics is non-linear, stochastic and particularly non-gradient, i.e., the driving force can not be written as gradient…

Neurons and Cognition · Quantitative Biology 2024-12-05 Junbin Qiu , Haiping Huang

A dynamics between Newton and Langevin formalisms is elucidated within the framework of the generalized Langevin equation. For thermal noise yielding a vanishing zero-frequency friction the corresponding non-Markovian Brownian dynamics…

Statistical Mechanics · Physics 2007-07-23 Jing-Dong Bao , Yi-Zhong Zhuo , Fernando A. Oliveira , Peter Hanggi

We use a Hamiltonian dynamics to discuss the statistical mechanics of long-lasting quasi-stationary states particularly relevant for long-range interacting systems. Despite the presence of an anomalous single-particle velocity distribution,…

Statistical Mechanics · Physics 2009-11-11 Fulvio Baldovin , Enzo Orlandini

Long-range interacting Hamiltonian systems are believed to relax generically towards non-equilibrium states called "quasi-stationary" because they evolve towards thermodynamic equilibrium very slowly, on a time-scale diverging with particle…

Statistical Mechanics · Physics 2017-07-18 Michael Joyce , Jules Morand , Pascal Viot

We investigate the asymptotic distributions of periodically driven anharmonic Langevin systems. Utilizing the underlying $SL_2$ symmetry of the Langevin dynamics, we develop a perturbative scheme in which the effect of periodic driving can…

Statistical Mechanics · Physics 2021-06-30 Shakul Awasthi , Sreedhar B. Dutta

We introduce new Langevin-type equations describing the rotational and translational motion of rigid bodies interacting through conservative and non-conservative forces, and hydrodynamic coupling. In the absence of non-conservative forces…

Computational Physics · Physics 2017-12-14 Ruslan L. Davidchack , Thomas E. Ouldridge , Michael V. Tretyakov

We study the Langevin dynamics of a ferromagnetic Ginzburg-Landau Hamiltonian with a competing long-range repulsive term in the presence of an external magnetic field. The model is analytically solved within the self consistent Hartree…

We consider the problem of inferring the dynamics of unknown (i.e. hidden) nodes from a set of observed trajectories and study analytically the average prediction error and the typical relaxation time of correlations between errors. We…

Disordered Systems and Neural Networks · Physics 2017-06-23 Barbara Bravi , Peter Sollich