ML SION1: Difference between revisions
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{{TAGDEF|ML_SION1|[real]|0.5}} | {{TAGDEF|ML_SION1|[real]|0.5}} | ||
Description: This tag specifies the width <math>\sigma_\text{atom}</math> of the Gaussian functions used for broadening the atomic distributions of the radial descriptor <math>\rho^{(2)}_i(r)</math> 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 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> | |||
and <math>g\left(\mathbf{r}\right)</math> is the following approximation of the delta function: | |||
<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_SION1}} 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_SION1}} is <math>\AA</math>. | The unit of {{TAG|ML_SION1}} is <math>\AA</math>. | ||
== Related Tags and Sections == | == Related Tags and Sections == |
Revision as of 11:37, 13 October 2021
ML_SION1 = [real]
Default: ML_SION1 = 0.5
Description: This tag specifies the width [math]\displaystyle{ \sigma_\text{atom} }[/math] of the Gaussian functions used for broadening the atomic distributions of the radial descriptor [math]\displaystyle{ \rho^{(2)}_i(r) }[/math] within the machine learning force field method.
The radial descriptor is constructed from
[math]\displaystyle{ \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]
and [math]\displaystyle{ g\left(\mathbf{r}\right) }[/math] is the following approximation of the delta function:
[math]\displaystyle{ 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 ML_SION1 sets the width [math]\displaystyle{ \sigma_\text{atom} }[/math] 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_SION1 is [math]\displaystyle{ \AA }[/math].
Related Tags and Sections
ML_LMLFF, ML_SION2, ML_RCUT1, ML_RCUT2, ML_MRB1, ML_MRB2