Hoellmer Qin Faulkner Maggs Krauth 2019

From Werner KRAUTH

(Difference between revisions)
Jump to: navigation, search
Revision as of 15:13, 5 February 2020
Werner (Talk | contribs)

← Previous diff
Revision as of 15:14, 5 February 2020
Werner (Talk | contribs)

Next diff →
Line 5: Line 5:
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. 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 [https://doi.org/10.1016/j.cpc.2020.107168 doi]''' (awaiting full bibliographic references).+'''Computer Physics Communications [https://doi.org/10.1016/j.cpc.2020.107168 2020]''' (open-source paper, awaiting full bibliographic references).
[http://arxiv.org/pdf/1907.12502 Electronic version (from arXiv)] [http://arxiv.org/pdf/1907.12502 Electronic version (from arXiv)]
[https://github.com/jellyfysh GitHub site of the JeLLyFysh organization, from which the open-source application can be forked (that is, downloaded)] [https://github.com/jellyfysh GitHub site of the JeLLyFysh organization, from which the open-source application can be forked (that is, downloaded)]

Revision as of 15:14, 5 February 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)

GitHub site of the JeLLyFysh organization, from which the open-source application can be forked (that is, downloaded)

Personal tools