ML WTOTEN: Difference between revisions

Latest revision as of 08:17, 3 October 2023

Default: ML_WTOTEN	= 0.005	if ML_IWEIGHT=1
	= 1.0	otherwise

Description: Sets a scaling of the fitted potential energy.

For ML_IWEIGHT=2 and 3 (default), the potential energy in the training data set is multiplied by ML_WTOTEN (unitless). We recommend increasing ML_WTOTEN if you plan to apply the force field in a simulation where the accuracy of the total energy is most important. This puts a focus on the energy error and is desirable, for instance, for the computation of defect-formation energies.

For ML_IWEIGHT=1, ML_WTOTEN has the unit of eV/atom, and the potential energy in the training data set is divided by it.

@@ Line 3: / Line 3: @@
 {{DEF|ML_WTOTEN|0.005|if {{TAG|ML_IWEIGHT}}{{=}}1|1.0|otherwise}}
-Description: This tag sets the weight for the scaling of the total energy in the training data within the machine learning force field method.
+Description: Sets a scaling of the fitted potential energy.
 ----
-{{TAG|ML_IWEIGHT}}, {{TAG|ML_WTOTEN}}, {{TAG|ML_WTIFOR}}, {{TAG|ML_WTSIF}} form a group of tags which set the normalization and weighting of ab initio training data, i.e.  energies, forces and stresses of the training structures. The main control tag is {{TAG|ML_IWEIGHT}}, please also have a look at its detailed description. If {{TAG|ML_IWEIGHT}}=1 the weight has a unit of eV/atom and is used to divide the data by it. For {{TAG|ML_IWEIGHT}}=2 and 3 the weights are unitless and the data is multiplied by the weight.
+For {{TAG|ML_IWEIGHT}}=2 and 3 (default), the potential energy in the training data set is multiplied by {{TAG|ML_WTOTEN}} (unitless). We recommend increasing {{TAG|ML_WTOTEN}} if you plan to apply the force field in a simulation where the accuracy of the total energy is most important. This puts a focus on the energy error and is desirable, for instance, for the computation of defect-formation energies.
+For {{TAG|ML_IWEIGHT}}=1, {{TAG|ML_WTOTEN}} has the unit of eV/atom, and the potential energy in the training data set is divided by it.
 == Related tags and articles ==
-{{TAG|ML_LMLFF}}, {{TAG|ML_IWEIGHT}}, {{TAG|ML_WTIFOR}}, {{TAG|ML_WTSIF}}, {{TAG|ML_IALGO_LINREG}}
+{{TAG|ML_IWEIGHT}}, {{TAG|ML_WTIFOR}}, {{TAG|ML_WTSIF}}, {{TAG|ML_IALGO_LINREG}}, {{TAG|ML_LMLFF}}
 {{sc|ML_WTOTEN|Examples|Examples that use this tag}}
 ----
-[[Category:INCAR tag]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]]
+[[Category:INCAR tag]][[Category:Machine-learned force fields]]