ML_CTIFOR
| Default: ML_CTIFOR | = 0.002 | if ML_CALGO = 0 |
| = 0.02 | if ML_CALGO = 1 |
Description: This flag sets the threshold for the error estimation in the machine learning force field method.
The use of this tag in combination with the learning algorithms is described here: here. Generally, first principles calculations are only performed if the error estimate of one force exceeds the threshold.
The initial threshold is set to the value provided by the tag ML_CTIFOR (units of eV/Angstrom for ML_CALGO=0 and unitless for ML_CALGO=1).
For ML_CALGO=0, the threshold can be updated dynamically during ML. The details of the update are controlled by ML_ICRITERIA. Typically, after extensive training, attainable values for ML_CTIFOR are 0.02 around 300-500 K, and 0.06 around 1000-2000 K, so temperature but also system dependent. The initial default 0.002 is only sensible, if ML_CTIFOR is automatically updated (ML_ICRITERIA = 1 or 2). If ML_ICRITERIA = 0 is used, it is necessary to use significantly larger values around 0.02-0.06 for ML_CTIFOR.
For ML_CALGO=1, only a constant threshold during the calculation is available (ML_ICRITERIA=0).
The related tag ML_SCLC_CTIFOR determines how many local reference configurations are chosen from each first principles calculations.
Related tags and articles
ML_LMLFF, ML_ICRITERIA, ML_CALGO, ML_SCLC_CTIFOR , ML_MHIS, ML_CSIG, ML_CSLOPE, ML_CDOUB, ML_CX, ML_NMDINT, ML_MCONF_NEW