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The generalized Langevin equation is a model for the motion of coarse-grained particles where dissipative forces are represented by a memory term. The numerical realization of such a model requires the implementation of a stochastic…

Soft Condensed Matter · Physics 2021-05-26 Niklas Bockius , Jeanine Shea , Gerhard Jung , Friederike Schmid , Martin Hanke

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 paper describes two iterative algorithms for solving general systems of M simultaneous linear algebraic equations (SLAE) with real matrices of coefficients. The system can be determined, underdetermined, and overdetermined. Linearly…

Numerical Analysis · Mathematics 2025-10-20 A. S. Kondratiev , N. P. Polishchuk

Many coarse-grained models have been developed for equilibrium studies of lipid bilayer membranes. To achieve in simulations access to length-scales and time-scales difficult to attain in fully atomistic molecular dynamics, these…

Soft Condensed Matter · Physics 2023-02-28 Yaohong Wang , Jon Karl Sigurdsson , Paul J. Atzberger

We develop further ideas on how to construct low-dimensional models of stochastic dynamical systems. The aim is to derive a consistent and accurate model from the originally high-dimensional system. This is done with the support of centre…

chao-dyn · Physics 2008-02-03 Chao Xu , A. J. Roberts

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

We propose a new model of turbulence for use in large-eddy simulations (LES). The turbulent force, represented here by the turbulent Lamb vector, is divided in two contributions. The contribution including only subfilter fields is…

Fluid Dynamics · Physics 2009-11-11 Jean-Philippe Laval , Berengere Dubrulle

Deep learning applications require global optimization of non-convex objective functions, which have multiple local minima. The same problem is often found in physical simulations and may be resolved by the methods of Langevin dynamics with…

Machine Learning · Statistics 2021-05-24 Oleksandr Borysenko , Maksym Byshkin

We report a hybrid numerical method for the solution of the model H fluctuating hydrodynamic equations for binary mixtures. The momentum conservation equations with Landau-Lifshitz stresses are solved using the fluctuating lattice Boltzmann…

Statistical Mechanics · Physics 2011-10-27 P. T. Sumesh , Ignacio Pagonabarraga , Ronojoy Adhikari

In the field of machine learning coarse-grained potentials in molecular dynamics, many propagators require that the effective Hamiltonian is quadratic in momentum, thus limiting the family of coarse-graining functions. In this paper, we…

Chemical Physics · Physics 2025-12-10 Andy Bruce , Alexander Aghili , Razvan Marinescu , Daniel Sabo

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 introduce a machine learning-based approach called ab initio generalized Langevin equation (AIGLE) to model the dynamics of slow collective variables in materials and molecules. In this scheme, the parameters are learned from atomistic…

Computational Physics · Physics 2024-04-02 Pinchen Xie , Roberto Car , Weinan E

D-dimensional constrained systems are studied with stochastic Lagrangian and\break Hamiltonian. It is shown that stochastic consistency conditions are second class constraints and Lagrange multiplier fields can be determined in…

High Energy Physics - Theory · Physics 2017-02-01 R. Mochizuki , K. Yoshida

We generalize the oscillator model of a particle interacting with a thermal reservoir by introducing arbitrary nonlinear couplings in the particle coordinates.The equilibrium positions of the heat bath oscillators are promoted to space-time…

High Energy Physics - Theory · Physics 2009-10-28 F. Illuminati , M. Patriarca , P. Sodano

We consider a discrete-time voter model process on a set of nodes, each being in one of two states, either 0 or 1. In each time step, each node adopts the state of a randomly sampled neighbor according to sampling probabilities, referred to…

Optimization and Control · Mathematics 2022-11-28 Milan Vojnovic , Kaifang Zhou

We present a derivation of a coarse-grained model from the Langevin dynamics. The focus is placed on the memory kernel function and the fluctuation-dissipation theorem. Also presented is an hierarchy of approximations for the memory and…

Numerical Analysis · Mathematics 2019-10-04 Lina Ma , Xiantao Li , Chun Liu

Extensions of the standard model that lead to first-order phase transitions in the early universe can produce a stochastic background of gravitational waves, which may be accessible to future detectors. Thermodynamic observables at the…

High Energy Physics - Lattice · Physics 2023-01-11 David Mason , Biagio Lucini , Maurizio Piai , Enrico Rinaldi , Davide Vadacchino

We present a theoretical investigation of a three-level $\Lambda$-type atom driven by a strong coherent laser and a weak stochastic field exhibiting amplitude and phase fluctuations. The stochastic field is modeled as a complex…

Quantum Physics · Physics 2025-12-29 Sajad Ahmadi , Mohsen Akbari , Shahpoor Saeidian , Ali Motazedifard

We propose a general method for simplifying master equations by eliminating from the description rapidly evolving states. The physical recipe we impose is the suppression of these states and a renormalization of the rates of all the…

Soft Condensed Matter · Physics 2008-04-20 Simone Pigolotti , Angelo Vulpiani

We derive exact Langevin-type equations governing quasispecies dynamics. The inherent multiplicative noise has both real and imaginary parts. The numerical simulation of the underlying complex stochastic partial differential equations is…

Statistical Mechanics · Physics 2007-05-23 David Hochberg , M. -P. Zorzano , Federico Moran
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