# Hoellmer Qin Faulkner Maggs Krauth 2019

### From Werner KRAUTH

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- | '''P. Hoellmer, L. Qin, M. F. Faulkner, A. C. Maggs, W. Krauth''' '''''JeLLyFysh-Version1.0 -- a Python application for all-atom event-chain Monte Carlo''''' ''' Physical Review B 99 064435 (2019)''' | + | '''P. Hoellmer, L. Qin, M. F. Faulkner, A. C. Maggs, W. Krauth''' '''''JeLLyFysh-Version1.0 -- a Python application for all-atom event-chain Monte Carlo''''' ''' (2020)''' |

=Paper= | =Paper= |

## Revision as of 14:29, 24 April 2020

**P. Hoellmer, L. Qin, M. F. Faulkner, A. C. Maggs, W. Krauth** **JeLLyFysh-Version1.0 -- a Python application for all-atom event-chain Monte Carlo**** (2020)**

# Paper

**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.

**Computer Physics Communications 2020** (open-source paper, awaiting full bibliographic references).

Electronic version (from arXiv)

https://github.com/jellyfysh GitHub repertory, from which the project may be forked.