ML SION2: Difference between revisions

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{{TAGDEF|ML_FF_SION2_MB|[real]}}
{{DISPLAYTITLE:ML_SION2}}
{{DEF|ML_FF_SION2_MB|none|if {{TAG|ML_FF_IBROAD2_MB}}{{=}}1|0.5|otherwise}}
{{TAGDEF|ML_SION2|[real]|{{TAG|ML_SION1}}}}


Description: This tag specifies the width of the Gaussian functions used for broadening the atomic distributions of the angular descriptor within the machine learning force field method.
Description: This tag specifies the width <math>\sigma_\text{atom}</math> of the Gaussian functions used for broadening the atomic distributions of the angular descriptor <math>\rho^{(3)}_i(r)</math> within the machine learning force field method.
----
----
The angular descriptor is constructed from


This tag is only set if {{TAG|ML_FF_IBROAD2_MB}} is not equal 1. The unit of {{TAG|ML_FF_SION2_MB}} is in <math>\AA</math>.
<math>
\rho_{i}^{(3)}\left(r,s,\theta\right) = \iint d\hat{\mathbf{r}} d\hat{\mathbf{s}}  \delta\left(\hat{\mathbf{r}}\cdot\hat{\mathbf{s}} - \mathrm{cos}\theta\right) \sum\limits_{j=1}^{N_{a}} \sum\limits_{k \ne j}^{N_{a}} \rho_{ik} \left(r\hat{\mathbf{r}}\right) \rho_{ij} \left(s\hat{\mathbf{s}}\right), \quad \text{where} \quad
\rho_{ij}\left(\mathbf{r}\right) = f_{\mathrm{cut}}\left(r_{ij}\right) g\left(\mathbf{r}-\mathbf{r}_{ij}\right)
</math>


== Related Tags and Sections ==
and <math>g\left(\mathbf{r}\right)</math> is the following approximation of the delta function:
{{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_SION1_MB}}, {{TAG|ML_FF_IBROAD1_MB}}, {{TAG|ML_FF_IBROAD2_MB}}


{{sc|ML_FF_SION2_MB|Examples|Examples that use this tag}}
<math>
g\left(\mathbf{r}\right)=\frac{1}{\sqrt{2\sigma_{\mathrm{atom}}\pi}}\mathrm{exp}\left(-\frac{|\mathbf{r}|^{2}}{2\sigma_{\mathrm{atom}}^{2}}\right).
</math>
 
The tag {{TAG|ML_SION2}} sets the width <math>\sigma_\text{atom}</math> of the above Gaussian function (see [[Machine learning force field: Theory#Descriptors|this section]] for more details).
{{BOX|tip|Our test calculations indicate that {{TAG|ML_SION1}} {{=}} {{TAG|ML_SION2}} results in an optimal training performance. Furthermore, a value of 0.5 was found to be a good default value for both. However, the best choice is system-dependent, careful testing may improve machine learning results.}}
The unit of {{TAG|ML_SION2}} is <math>\AA</math>.
 
== Related tags and articles ==
{{TAG|ML_LMLFF}}, {{TAG|ML_SION1}}, {{TAG|ML_RCUT1}}, {{TAG|ML_RCUT2}}, {{TAG|ML_MRB1}}, {{TAG|ML_MRB2}}
 
{{sc|ML_SION2|Examples|Examples that use this tag}}
----
----


[[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category:VASP6]]
[[Category:INCAR tag]][[Category:Machine-learned force fields]]

Latest revision as of 13:31, 8 April 2022

ML_SION2 = [real]
Default: ML_SION2 = ML_SION1 

Description: This tag specifies the width of the Gaussian functions used for broadening the atomic distributions of the angular descriptor within the machine learning force field method.


The angular descriptor is constructed from

and is the following approximation of the delta function:

The tag ML_SION2 sets the width of the above Gaussian function (see this section for more details).

Tip: Our test calculations indicate that ML_SION1 = ML_SION2 results in an optimal training performance. Furthermore, a value of 0.5 was found to be a good default value for both. However, the best choice is system-dependent, careful testing may improve machine learning results.

The unit of ML_SION2 is .

Related tags and articles

ML_LMLFF, ML_SION1, ML_RCUT1, ML_RCUT2, ML_MRB1, ML_MRB2

Examples that use this tag