ML MRB1: Difference between revisions
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{{TAGDEF| | {{DISPLAYTITLE:ML_MRB1}} | ||
{{TAGDEF|ML_MRB1|[integer]|12}} | |||
Description: | Description: This tag sets the number <math>N_\text{R}^0</math> of radial basis functions used to expand the radial descriptor <math>\rho^{(2)}_i(r)</math> within the machine learning force field method. | ||
---- | ---- | ||
The radial descriptor is constructed from | |||
== | <math> | ||
\rho_{i}^{(2)}\left(r\right) = \frac{1}{4\pi} \int \rho_{i}\left(r\hat{\mathbf{r}}\right) d\hat{\mathbf{r}}, \quad \text{where} \quad | |||
\rho_{i}\left(\mathbf{r}\right) = \sum\limits_{j=1}^{N_{\mathrm{a}}} f_{\mathrm{cut}}\left(r_{ij}\right) g\left(\mathbf{r}-\mathbf{r}_{ij}\right) | |||
</math> | |||
{{sc| | and <math>g\left(\mathbf{r}\right)</math> is an approximation of the delta function. In practice, the continuous function above is transformed into a discrete set of numbers by expanding it into a set of radial basis functions <math>\chi_{n0}(r)</math> (see [[Machine learning force field: Theory#Basis set expansion|this section]] for more details): | ||
<math> | |||
\rho_{i}^{(2)}\left(r\right) = \frac{1}{\sqrt{4\pi}} \sum\limits_{n=1}^{N^{0}_{\mathrm{R}}} c_{n00}^{i} \chi_{n0}\left(r\right). | |||
</math> | |||
The tag {{TAG|ML_MRB1}} sets the number <math>N_\text{R}^0</math> of radial basis functions to use in this expansion. | |||
== Related tags and articles == | |||
{{TAG|ML_LMLFF}}, {{TAG|ML_MRB2}}, {{TAG|ML_W1}}, {{TAG|ML_RCUT1}}, {{TAG|ML_SION1}} | |||
{{sc|ML_MRB1|Examples|Examples that use this tag}} | |||
---- | ---- | ||
[[Category:INCAR]][[Category:Machine | [[Category:INCAR tag]][[Category:Machine-learned force fields]] |
Latest revision as of 08:06, 9 May 2023
ML_MRB1 = [integer]
Default: ML_MRB1 = 12
Description: This tag sets the number of radial basis functions used to expand the radial descriptor within the machine learning force field method.
The radial descriptor is constructed from
and is an approximation of the delta function. In practice, the continuous function above is transformed into a discrete set of numbers by expanding it into a set of radial basis functions (see this section for more details):
The tag ML_MRB1 sets the number of radial basis functions to use in this expansion.
Related tags and articles
ML_LMLFF, ML_MRB2, ML_W1, ML_RCUT1, ML_SION1