ML SCLC CTIFOR: Difference between revisions
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Description: Sets fraction by which the Bayesian threshold for the maximum forces is lowered in the selection of local reference calculations. | Description: Sets fraction by which the Bayesian threshold for the maximum forces is lowered in the selection of local reference calculations. | ||
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At every sampling step each atom with it's environment is chosen as a local reaference configuration is chosen if it's predicted error in the force is larger than the Bayesian threshold for the maximum forces ({{TAG|ML_CTIFOR}}. {{TAG|ML_SCLC_CTIFOR}} lowers the threshold by multiplying it to {{TAG|ML_CTIFOR}}, but it doesn't effect the decision whether a sampling step (ab-initio calculation) is carried out or not, since the decision for sampling is done previously in a separate step. | At every sampling step each atom with it's environment is chosen as a local reaference configuration is chosen if it's predicted error in the force is larger than the Bayesian threshold for the maximum forces ({{TAG|ML_CTIFOR}}). {{TAG|ML_SCLC_CTIFOR}} lowers the threshold by multiplying it to {{TAG|ML_CTIFOR}}, but it doesn't effect the decision whether a sampling step (ab-initio calculation) is carried out or not, since the decision for sampling is done previously in a separate step. | ||
The default value of 0.8 was set by us empirically in dependence of default values for other input parameters. | The default value of 0.8 was set by us empirically in dependence of default values for other input parameters. | ||
Revision as of 11:34, 6 May 2022
ML_IREG = [real]
Default: ML_IREG = 0.8
Description: Sets fraction by which the Bayesian threshold for the maximum forces is lowered in the selection of local reference calculations.
At every sampling step each atom with it's environment is chosen as a local reaference configuration is chosen if it's predicted error in the force is larger than the Bayesian threshold for the maximum forces (ML_CTIFOR). ML_SCLC_CTIFOR lowers the threshold by multiplying it to ML_CTIFOR, but it doesn't effect the decision whether a sampling step (ab-initio calculation) is carried out or not, since the decision for sampling is done previously in a separate step.
The default value of 0.8 was set by us empirically in dependence of default values for other input parameters.
We don't recommend the user to change this value.
Related tags and articles
ML_LMLFF, ML_CTIFOR, ML_CX, ML_EPS_LOW