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QMCBlip

QMCBlip allows to couple Quantum Monte Carlo Simulations with Machine Learning Force Fields to accelerate Molecular Dynamics simulations

3
contributors

What QMCBlip can do for you

  • user friendly
  • interface to ML Force FLARE, FLARE++, sGDML
  • interface to QMC packages such as CHAMP and QMCTorch

Driving molecular dynamic simulation with quantum monte carlo calculations of the atomic forces is computationally expensive. QMCBlip allows to train machine learning force fields on the fly to reduce the computational requirements of such calculations. QMCBlip was developed during the internship of Emiel Slootman in collaboration with Claudia Filippi from University of Twente.

Keywords
No keywords avaliable
Programming language
  • Python 100%
License
  • Apache-2.0
</>Source code

Participating organisations

University of Twente
Netherlands eScience Center

Contributors

Contact person

Nicolas Renaud

Nicolas Renaud

Netherlands eScience Center
ES
Emiel Slootman
University of Twente
CF
Claudia Filippi
University of Twente
Nicolas Renaud
Nicolas Renaud
Netherlands eScience Center

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