ML MRB1: Difference between revisions

From VASP Wiki
No edit summary
No edit summary
Line 10: Line 10:
</math>
</math>


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_{nl}(r)</math> (see [[Machine learning force field: Theory#Basis set expansion|this section]] for more details):
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>
<math>
\rho_{i}^{(2)}\left(r\right) = \frac{1}{\sqrt{4\pi}} \sum\limits_{n=1}^{N^{0}_{\mathrm{R}}} c_{n00}^{i} \chi_{nl}\left(r\right).
\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>
</math>



Revision as of 12:55, 13 October 2021

ML_MRB1 = [integer]
Default: ML_MRB1 = 8 

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. The value of ML_MRB1 is the default value for ML_MRB2.

Related Tags and Sections

ML_LMLFF, ML_MRB2, ML_W1, ML_RCUT1, ML_SION1

Examples that use this tag