Michael Faulkner

Michael Faulkner

Computational statistical physicist specialising in phase transitions, planar systems, electrostatics and Monte Carlo sampling algorithms

JeLLyFysh-Version1.0 — a Python application for all-atom event-chain Monte Carlo

Published in Comput. Phys. Commun., 2020

Recommended citation: Comput. Phys. Commun. 253, 107168 (2020)

Philipp Höllmer, Liang Qin, Michael F. Faulkner, Anthony C. Maggs and Werner Krauth

Links: arXiv and DOI.

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 mirrors the mathematical formulation of ECMC. Local potentials, long-range 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.