Neural network force field computational algorithms for molecular dynamics computer simulations

A non-transitory computer-readable medium tangibly embodying computer readable instructions for a software program, the software program being executable by a processor of a computing device to provide operations comprising:

• receiving a combination of a number of rotationally-invariant features and a number of rotationally-covariant features of a local environment of a multi-element system having elements;
• predicting a force vector for each element within the multi-element system based on the combination of the number of rotationally-invariant features and the number of rotationally-covariant features, and a neural network force field (NNFF), to obtain a simulated motion of the elements within the multi-element system;
• and
• training a first neural network (NN1) based on the number of rotationally-invariant features to predict a number of rotationally-invariant intermediate states.

A computer system for simulating the motion of elements within a multi-element system using a neural network force field (NNFF) including a simulation computer having a processor for executing computer-readable instructions and a memory for maintaining the computer-executable instructions, the computer-executable instructions when executed by the processor perform the following functions:

• receiving a combination of a number of rotationally-invariant features and a number of rotationally-covariant features of a local environment of the multi-element system having elements;
• predicting a force vector for each element within the multi-element system based on the combination of the number of rotationally-invariant features and the number of rotationally-covariant features, and the NNFF, to obtain a simulated motion of the elements within the multi-element system;
• and
• training a first neural network (NN1) based on the number of rotationally-invariant features to predict a number of rotationally-invariant intermediate states.