Hybrid Monte Carlo with LAMMPS
JX Guo and A Haji-Akbari and JC Palmer, JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY, 17, 1840002 (2018).
We describe a strategy for performing canonical and isothermal-isobaric ensemble hybrid Monte Carlo (HMC) simulations with the widely-used Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) molecular dynamics (MD) software package. The overall workflow for the HMC simulations is handled using an external Python driver script, which invokes LAMMPS' library interface to perform numerically intensive tasks such as MD integration. We document several rigorous consistency checks that have been used to validate our HMC implementation. We also demonstrate that our approach can be readily extended to implement biased HMC sampling schemes for computing free energies. Codes and input files from the documented examples are available on the web.
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