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

Published: 6 Feb 2020 | Version 1 | DOI: 10.17632/srrjt9493d.1
Contributor(s):
  • Philipp Höllmer,
    Philipp Höllmer
    Laboratoire de Physique de l’Ecole normale superieure, ENS, Universite PSL, CNRS, Sorbonne Universite, Universite Paris-Diderot
  • Liang Qin,
    Liang Qin
    Laboratoire de Physique de l’Ecole normale superieure, ENS, Universite PSL, CNRS, Sorbonne Universite, Universite Paris-Diderot
  • Michael F. Faulkner,
    Michael F. Faulkner
    University of Bristol
  • A.C. Maggs,
    A.C. Maggs
    CNRS UMR7083, ESPCI Paris, PSL Research University
  • Werner Krauth
    Werner Krauth
    Laboratoire de Physique de l’Ecole normale superieure, ENS, Universite PSL, CNRS, Sorbonne Universite, Universite Paris-Diderot

Description of this data

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-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.

Experiment data files

This data is associated with the following publication:

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

Published in: Computer Physics Communications

Latest version

  • Version 1

    2020-02-06

    Published: 2020-02-06

    DOI: 10.17632/srrjt9493d.1

    Cite this dataset

    Höllmer, Philipp; Qin, Liang; Faulkner, Michael F.; Maggs, A.C.; Krauth, Werner (2020), “JeLLyFysh-Version1.0 - a Python application for all-atom event-chain Monte Carlo”, Mendeley Data, v1 http://dx.doi.org/10.17632/srrjt9493d.1

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Downloads: 2

Categories

Computational Physics, Markov Chain, Application of Monte Carlo Method

Licence

GPLv3 Learn more

The files associated with this dataset are licensed under a GNU Public License Version 3 licence.

What does this mean?
The GNU General Public License is a free, copyleft license for software and other kinds of works.

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