JeLLyFysh-Version1.0 -- a Python application for all-atom event-chain Monte Carlo
Computational Physics
2020-11-13 v1 Statistical Mechanics
Abstract
We present JeLLyFysh-Version1.0, an open-source Python application for event-chain Monte Carlo (ECMC), an event-driven irreversible Markov-chain Monte Carlo algorithm for classical N-body simulations in statistical mechanics, biophysics and electrochemistry. The application's architecture closely mirrors the mathematical formulation of ECMC. Local potentials, long-ranged Coulomb interactions and multi-body bending potentials are covered, as well as bounding potentials and cell systems including the cell-veto algorithm. Configuration files illustrate a number of specific implementations for interacting atoms, dipoles, and water molecules.
Cite
@article{arxiv.1907.12502,
title = {JeLLyFysh-Version1.0 -- a Python application for all-atom event-chain Monte Carlo},
author = {Philipp Hoellmer and Liang Qin and Michael F. Faulkner and A. C. Maggs and Werner Krauth},
journal= {arXiv preprint arXiv:1907.12502},
year = {2020}
}
Comments
47 pages, 17 figures