This page contains the code from the paper
"Combining machine-learned and classical force fields with the parareal algorithm: application to the diffusion of atomistic defects"
by Olga Gorynina, Frédéric Legoll, Tony Lelièvre and Danny Perez
-Python 3.8+
-Compile LAMMPS as a shared library with python support: https://docs.lammps.org/Python_install.html
python run.py [options]
--N: Number of time steps in parareal algorithm (default value 2000)
--fine: choice of potential for fine propagator (default value 14, corresponds to SNAP-205 potential)
availible potentials:
14 - SNAP-205
12 - SNAP-141
10 - SNAP-92
8 - SNAP-56
6 - SNAP-31
4 - SNAP-15
2 - SNAP-6
0 - EAM potential
--coarse: choice of potential for coarse propagator (default value 0, corresponds to EAM potential)
--dc: convergence parameter (default value 10^(-5))
--de: explosion threshold parameter, de > dc (default value 0.35)