The typical use of
RuNNer consists of three steps called modes:
mode 1: Transformation of the Cartesian coordinates to symmetry functions, splitting of the reference data into a training and a test set, and the conversion of total energies in energies per atom (and removing the free atom energies, if requested).
mode 2: Analysis of the training and test sets and determination of the NN parameters in an iterative optimization process.
mode 3: Application of the potential to predict energies, forces, stress tensors and charges. Currently
RuNNeris mainly used for calculating these properties for multiple given structures.
RuNNeris not a molecular dynamics code. For MD, a compatible implementation in LAMMPS is available, which can use NN potentials constructed with
Mode 1: Generation of the Symmetry Functions
In mode 1 the symmetry functions are generated from the structural information
provided in the
input.data file. The generation of the symmetry functions is
not parallelized as even for different fits the generation has to be done only
once with reasonable CPU time requirements. It needs to be repeated only if the
symmetry functions or the splitting into the training and test sets (cf. keyword
Relevant files to get you started
Only two files are needed by RuNNer in order to start calculating symmetry functions:
Mode 2: Fitting
In mode 2 the weight parameters of the atomic neural networks are determined.
Mode 3: Application of the Neural Network Potential
In mode 3 the finalized NNP can be used to predict the energies and forces of a
single structure given in the
input.data file. If there is more than one
structure included in the
input.data file, all structures in