ML_SIGW0

ML_SIGW0 = [real]
Default: none

Default: ML_SIGW0	= 1E-7	for ML_MODE = REFIT
	= 1.0	else

Description: This flag sets the precision parameter $s_{\mathrm {w} }$ (see here for definition) for the fitting in the machine learning force field method.

The default value for ML_MODE=REFIT works reliably in most calculations, however, sometimes it is necessary to increase the regularization parameter to avoid instabilities during finite temperature molecular dynamics simulations.

Suppose the regularization needs to be controlled manually, like e.g. in the fitting via singular value decomposition (ML_MODE=REFIT or ML_IALGO_LINREG=4). The best is to control the regularization via this parameter and keep the noise parameter $s_{\mathrm {v} }$ (see ML_SIGV0) constant at 1. Useful values for ML_SIGW0 are typically between 1E-1 and 1E-9. When the value is increased the regularization is increased. This often slightly increases the training set error but also reduces potential instabilities. Hence, if instabilities are observed during molecular-dynamics simulations, one should try to increase ML_SIGW0 to say 1E-2, then refit, and repeat the molecular-dynamics simulations.

More on the theory of this regularization parameter can be found in this section.

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