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 (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 253 107168 (2020) (open-access publication).

[1]

Electronic version (from arXiv)

https://github.com/jellyfysh GitHub repertory, from which the JellyFysh application may be forked or simply cloned.

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