ML SION1: Difference between revisions
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{{TAGDEF| | {{TAGDEF|ML_SION1_MB|[real]|0.333333}} | ||
Description: This tag specifies the width of the Gaussian functions used for broadening the atomic distributions for the radial descriptor within the machine learning force field method. | Description: This tag specifies the width of the Gaussian functions used for broadening the atomic distributions for the radial descriptor within the machine learning force field method. | ||
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The unit of {{TAG| | The unit of {{TAG|ML_SION1}} is in <math>\AA</math>. | ||
Test calculations showed that a 1.5 smaller value for the broadening of the radial descriptor compared to the angular descriptor (see {{TAG| | Test calculations showed that a 1.5 smaller value for the broadening of the radial descriptor compared to the angular descriptor (see {{TAG|ML_SION2}}) gives optimal results. | ||
The default value for {{TAG| | The default value for {{TAG|ML_SION1}} is chosen such that {{TAG|ML_SION2}} becomes 0.5. | ||
== Related Tags and Sections == | == Related Tags and Sections == | ||
{{TAG| | {{TAG|ML_LMLFF}}, {{TAG|ML_SION2}}, {{TAG|ML_RCUT1}}, {{TAG|ML_RCUT2}}, {{TAG|ML_MRB1}}, {{TAG|ML_MRB2}} | ||
{{sc| | {{sc|ML_SION1|Examples|Examples that use this tag}} | ||
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[[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]] | [[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]] |
Revision as of 11:04, 6 September 2021
ML_SION1_MB = [real]
Default: ML_SION1_MB = 0.333333
Description: This tag specifies the width of the Gaussian functions used for broadening the atomic distributions for the radial descriptor within the machine learning force field method.
The unit of ML_SION1 is in . Test calculations showed that a 1.5 smaller value for the broadening of the radial descriptor compared to the angular descriptor (see ML_SION2) gives optimal results. The default value for ML_SION1 is chosen such that ML_SION2 becomes 0.5.
Related Tags and Sections
ML_LMLFF, ML_SION2, ML_RCUT1, ML_RCUT2, ML_MRB1, ML_MRB2