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descriptor ρ i ( 2 ) ( r ) {\displaystyle \rho _{i}^{(2)}(r)} within the machine learning force field method. The radial descriptor is constructed from ρ i (...

(ML_CTIFOR) is updated within the machine learning force field methods. The use of this tag in combination with the learning algorithms is described here:...

Bayesian error estimation in the machine learning force field method. The usage of this tag in combination with the learning algorithms is described here:...

Bayesian error estimation in the machine learning force field method. The usage of this tag in combination with the learning algorithms is described here:...

number of structures stored in memory that are used for training in the machine learning force field method. The defaults for ML_MCONF are different for each...

radial basis functions used to expand the angular descriptor within the machine learning force field method. The angular descriptor is constructed from ρ i...

descriptor ρ i ( 3 ) ( r ) {\displaystyle \rho _{i}^{(3)}(r)} in the machine learning force field method. The unit of the cut-off radius is Å {\displaystyle...

descriptor ρ i ( 3 ) ( r ) {\displaystyle \rho _{i}^{(3)}(r)} within the machine learning force field method. The angular descriptor is constructed from ρ i...

{\displaystyle \beta } for the radial (and angular) descriptor within the machine learning force field method (see this section). The weight for the angular descriptor...

whether the regularization parameters are kept constant or not in the machine learning force field method. The following cases are possible for this tag:...

computation during on-the-fly learning: Do not set MAXMIX>0 when using force fields for machine learning. During machine learning, first-principles calculations...

weight for the scaling of the forces in the training data within the machine learning force field method. ML_IWEIGHT, ML_WTOTEN, ML_WTIFOR, ML_WTSIF form...

weight for the scaling of the stress in the training data within the machine learning force field method. ML_IWEIGHT, ML_WTOTEN, ML_WTIFOR, ML_WTSIF form...

s_{\mathrm {w} }} (see here for definition) for the fitting in the machine learning force field method. The default value for ML_MODE=REFIT works reliable...

filtering parameter for the angular filtering for ML_IAFILT2 in the machine learning force field method. This tag is only used if ML_LAFILT2=.TRUE. and...

tag selects the descriptor type of the three-body descriptor used in machine learning force fields. This tag selects how the three-body descriptor is calculated...

Description: This tag specifies how to scale the energy data in the machine learning force field method. The following cases are possible: ML_ISCALE_TOTEN...

how the Bayesian error threshold (ML_CTIFOR) is updated within the machine learning force field method. ML_CTIFOR determines whether a first-principles...

s_{\mathrm {v} }} (see here for definition) for the fitting in the machine learning force field method. If the regularization needs to be controlled manually...

activated in order to calculate the chemical potentials within the machine learning force field method. In thermodynamic integration a coupling parameter...

This binary file contains a knewly created force field from machine learning runs with the options ML_MODE=train, refit or select. It's structure is identical...

Description: This tag specifies the type of angular filtering used in the machine learning force field method. Fig. 1: Square of filtering function. This tag...

tag specifies whether angular filtering is applied or not within the machine learning force field method. For the desciption of the filters please see: ML_IAFILT2...

parameter for the calculation of the chemical potential within the machine learning force field method. For thermodynamic integration calculations please...

parameter is introduced to calculate the chemical potential within the machine learning force field method. Atom are ordered according to the POSCAR file and...

parameter is introduced to calculate the chemical potential within the machine learning force field method. For thermodynamic integration calculations please...

normalizing and weighting the energies, forces, and stresses in the machine learning force field method. To achieve optimal training it is important to...

the bug report. 6.4.1 6.4.0 2023-03-07 Output of memory estimate in machine learning force fields is wrong for SVD refitting: The SVD algorithm (ML_IALGO_LINREG=3...

to get training samples in the machine learning force field method. The usage of this tag in combination with the learning algorithms is described here:...

spherical harmonics used to expand atomic distributions within the machine learning force field method. To construct an atomic environment descriptor the...

on the descriptors for refitting in the fast execution mode within machine learning force fields. This tag is usually switched on by ML_MODE = refit and...

heat flux is calculated or not in the machine learning force field method. The heat flux within machine learning force fields is decomposed into atomic...

Overview >Liquid Si - MLFF > List of tutorials The tutorial is made of the following parts: Liquid Si - MLFF...

for the molecular-dynamics part. The electronic minimization or the machine learning tags have to be added....

polynomial power ζ {\displaystyle \zeta } of the kernel within the machine learning force field method (see this section). The value of ML_NHYP must be...

for the molecular-dynamics part. The electronic minimization or the machine learning tags have to be added....

Description: Reference total energies of isolated atoms used in the machine learning force field method. This tag is only used if ML_ISCALE_TOTEN = 1. If...

The main output files for the machine learning are ML_ABN contains the ab initio structure datasets used for the learning. It will be needed for continuation...

such that the velocities are determined by the Hellmann-Feynman forces or Machine-learned force fields only. See table for the corresponding MDALGO setting...

such that the velocities are determined by the Hellmann-Feynman forces or machine-learned force fields only. Setting the tag LANGEVIN_GAMMA_L = 0, removes...

traditional way. To learn more about on-the-fly machine learning read about the theory of on-the-fly machine learning force fields or about the setup of a basic...

(stdout, OUTCAR, REPORT for molecular-dynamics runs, ML_LOGFILE for machine-learning force fields, etc.) and any problem-specific files that, e.g., include...

computed. The machine-learning approach will be an approximation to the underlying method against which it was fitted. The machine learning force field decomposes...

initial MLFF guesses. Check maximum size of sysv shmem segments used in machine-learning-code paths. BSE algorithm has been optimized and ported to GPU by means...

In context of the machine-learned force fields method this file serves as an output for the collected training data set. When running VASP with ML_MODE...

written to the corresponding files (OUTCAR, OSZICAR, ML_LOGFILE, etc.). If learning is activated (ML_MODE=TRAIN, SELECT, REFIT or REFITBAYESIAN) the only allowed...

improves the initial learning efficiency but might slow the force-field calculations. So ML_SCLC_CTIFOR compromises either learning efficiency or the speed...

local reference configurations required for generation of a machine-learned force field. Machine-learned force fields based on the kernel method require a...