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

Philipp Höllmer, Liang Qin, Michael Faulkner, Anthony Maggs, Werner Krauth

Research output: Contribution to journalArticle (Academic Journal)peer-review

8 Citations (Scopus)


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
-body simulations in statistical mechanics, biophysics and electrochemistry. The application’s architecture 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.
Original languageEnglish
Pages (from-to)107168
JournalComput. Phys. Commun
Early online date20 Jan 2020
Publication statusPublished - Aug 2020


Dive into the research topics of 'JeLLyFysh-Version1.0 - a Python application for all-atom event-chain Monte Carlo'. Together they form a unique fingerprint.

Cite this