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

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. Program title:JeLLyFysh-Version1.0 Program files doi:http://dx.doi.org/10.17632/srrjt9493d.1 Licensing provisions: GNU GPLv3 Programming language: Python 3 Nature of problem: Event-chain Monte Carlo (ECMC) simulations for classical N-body simulations in statistical mechanics, biophysics and electrochemistry. Solution method: Event-driven irreversible Markov-chain Monte Carlo algorithm. Additional comments: The application is complete with sample configuration files, docstrings, and unittests. The manuscript is accompanied by a frozen copy of JeLLyFysh-Version1.0 that is made publicly available on GitHub (repository https://github.com/jellyfysh/JeLLyFysh, commit hash d453d497256e7270e8babc8e04d20fb6d847dee4).