ADMP

Automatic Differentiable Multipolar Polarizable (ADMP) force field calculator.

This module provides an auto-differentiable implementation of multipolar polarizable force fields, that resembles the behavior of MPID plugin of OpenMM. Supposedly, this module is developed for the following purposes:

1. Achieving an easy calculation of force and virial of the multipolar polarizable forcefield.
2. Allowing fluctuating (geometric-dependent) multipoles/polarizabilities in multipolar polarizable potentials.
3. Allowing the calculation of derivatives of various force field parameters, thus achieving a more systematic and automatic parameter optimization scheme.

The module is based on JAX and JAX-MD projects.

Installation

Dependencies

ADMP module depends on the following packages, install them before using ADMP:

1. Install jax (pick the correct cuda version, see more details on their installation guide):

   pip install jax[cuda11_cudnn82] -f https://storage.googleapis.com/jax-releases/jax_releases.html

2. Install jax-md :

   pip install jax-md --upgrade

   ADMP currently relies on the space and partition modules to provide neighbor list

3. Install ADMP:

   ADMP is a pure python module, just simply put it in your $PYTHONPATH.

   export PYTHONPATH=$PYTHONPATH:/path/to/admp	

Settings

In admp/settings.py, you can modify some global settings, including:

PRECISION: single or double precision

DO_JIT: whether do jit or not.

Example

We provide a MPID 1024 water box example. In water_1024 and water_pol_1024, we show both the nonpolarizable and the polarizable cases.

cd ./examples/water_1024
./run_admp.py

cd ./examples/water_pol_1024
./run_admp.py

if DO_JIT = True, then the first run would be a bit slow, since it tries to do the jit compilation. Further executions of get_forces or get_energy should be much faster.