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Related papers: Classical Langevin Dynamics for Model Hamiltonians

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The properties of molecules and materials containing light nuclei are affected by their quantum mechanical nature. Modelling these quantum nuclear effects accurately requires computationally demanding path integral techniques. Considerable…

Chemical Physics · Physics 2020-04-22 Venkat Kapil , David M. Wilkins , Jinggang Lan , Michele Ceriotti

This paper is the second in a series devoted to the study of Langevin systems subjected to a continuous time-delayed feedback control. The goal of our previous paper [Phys. Rev. E 91, 042114 (2015)] was to derive second-law-like…

Statistical Mechanics · Physics 2017-03-01 M. L. Rosinberg , G. Tarjus , T. Munakata

We reelaborate on a general method for obtaining effective Hamiltonians that describe different nonlinear optical processes. The method exploits the existence of a nonlinear deformation of the su(2) algebra that arises as the dynamical…

Quantum Physics · Physics 2009-11-07 A. B. Klimov , J. L. Romero , J. Delgado , L. L. Sanchez-Soto

By examining both the divergence of the velocity vector in orthogonal Cartesian coordinate space $\mathbf{\Gamma} $ of dimension $\R^{\textrm {2fN}}$ and the structure of the Hamiltonian determining a system trajectory, it is shown that the…

Chaotic Dynamics · Physics 2007-05-23 Christopher G. Jesudason

We revisit the hard-spheres lattice gas model in the spherical approximation proposed by Lebowitz and Percus (J. L. Lebowitz, J. K. Percus, Phys. Rev.{\ 144} (1966) 251). Although no disorder is present in the model, we find that the…

Materials Science · Physics 2009-10-30 F. G. Padilla , F. Ritort

We couple a nonlinear evolution equation with an associated one and derive the action principle. This allows us to write the Lagrangian density of the system in terms of the original field variables rather than Casimir potentials. We find…

Exactly Solvable and Integrable Systems · Physics 2007-06-13 Sk. Golam Ali , B. Talukdar , U. Das

This work proposes a model-reduction methodology that preserves Lagrangian structure (equivalently Hamiltonian structure) and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence.…

Computational Engineering, Finance, and Science · Computer Science 2015-04-16 Kevin Carlberg , Ray Tuminaro , Paul Boggs

We show how to find the physical Langevin equation describing the trajectories of particles undergoing collisionless stochastic acceleration. These stochastic differential equations retain not only one-, but two-particle statistics, and…

Mathematical Physics · Physics 2013-12-17 J. W. Burby , A. I. Zhmoginov , H. Qin

Recently there has been remarkable progress in the complex Langevin method, which aims at solving the complex action problem by complexifying the dynamical variables in the original path integral. In particular, a new technique called the…

High Energy Physics - Lattice · Physics 2015-12-30 Keitaro Nagata , Jun Nishimura , Shinji Shimasaki

We study the Langevin dynamics of diffusive particles with regular pairwise interactions under mean-field scaling. By approximating empirical distributions with conditional distributions, we establish coercive and contractive properties for…

Probability · Mathematics 2026-05-28 Songbo Wang

The measured time series from complex systems are renowned for their intricate stochastic behavior, characterized by random fluctuations stemming from external influences and nonlinear interactions. These fluctuations take diverse forms,…

Statistical Mechanics · Physics 2025-03-19 Pyei Phyo Lin , Matthias Wächter , Joachim Peinke , M. Reza Rahimi Tabar

Hamiltonian mechanics describes the evolution of a system through its Hamiltonian. The Hamiltonian typically also represents the energy observable, a Noether-conserved quantity associated with the time-invariance of the law of evolution. In…

Quantum Physics · Physics 2024-03-29 Libo Jiang , Daniel R. Terno , Oscar Dahlsten

Electronic friction and Langevin dynamics is a popular mixed quantum-classical method for simulating the nonadiabatic dynamics of molecules interacting with metal surfaces, as it can be computationally more efficient than fully quantum…

Chemical Physics · Physics 2024-06-06 Martin Mäck , Samuel L. Rudge , Michael Thoss

In this paper we address the problem of consistently construct Langevin equations to describe fluctuations in non-linear systems. Detailed balance severely restricts the choice of the random force, but we prove that this property together…

Condensed Matter · Physics 2007-05-23 J. Bonet Avalos , I. Pagonabarraga

We present a method for learning generalized Hamiltonian decompositions of ordinary differential equations given a set of noisy time series measurements. Our method simultaneously learns a continuous time model and a scalar energy function…

Machine Learning · Computer Science 2021-04-16 Kevin L. Course , Trefor W. Evans , Prasanth B. Nair

The evolution of finitely many particles obeying Langevin dynamics is described by Dean-Kawasaki equations, a class of stochastic equations featuring a non-Lipschitz multiplicative noise in divergence form. We derive a regularised…

Probability · Mathematics 2019-09-10 Federico Cornalba , Tony Shardlow , Johannes Zimmer

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…

Mixed quantum-classical models have been proposed in several contexts to overcome the computational challenges of fully quantum approaches. However, current models typically suffer from long-standing consistency issues, and, in some cases,…

Mathematical Physics · Physics 2023-07-21 Cesare Tronci , François Gay-Balmaz

We derive the dynamics of several rigid bodies of arbitrary shape in a 2-dimensional inviscid and incompressible fluid, whose vorticity field is given by point vortices. We adopt the idea of Vankerschaver et al. (2009) to derive the…

Fluid Dynamics · Physics 2014-02-27 Steffen Weissmann

The past few years have witnessed an increased interest in learning Hamiltonian dynamics in deep learning frameworks. As an inductive bias based on physical laws, Hamiltonian dynamics endow neural networks with accurate long-term…

Machine Learning · Computer Science 2022-03-02 Zhijie Chen , Mingquan Feng , Junchi Yan , Hongyuan Zha
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