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# ML SION1

ML_SION1 = [real]
Default: ML_SION1 = 0.5

Description: This tag specifies the width ${\displaystyle \sigma _{\text{atom}}}$ of the Gaussian functions used for broadening the atomic distributions of the radial descriptor ${\displaystyle \rho _{i}^{(2)}(r)}$ within the machine learning force field method.

The radial descriptor is constructed from

${\displaystyle \rho _{i}^{(2)}\left(r\right)={\frac {1}{4\pi }}\int \rho _{i}\left(r{\hat {\mathbf {r} }}\right)d{\hat {\mathbf {r} }},\quad {\text{where}}\quad \rho _{i}\left(\mathbf {r} \right)=\sum \limits _{j=1}^{N_{\mathrm {a} }}f_{\mathrm {cut} }\left(r_{ij}\right)g\left(\mathbf {r} -\mathbf {r} _{ij}\right)}$

and ${\displaystyle g\left(\mathbf {r} \right)}$ is the following approximation of the delta function:

${\displaystyle g\left(\mathbf {r} \right)={\frac {1}{\sqrt {2\sigma _{\mathrm {atom} }\pi }}}\mathrm {exp} \left(-{\frac {|\mathbf {r} |^{2}}{2\sigma _{\mathrm {atom} }^{2}}}\right).}$

The tag ML_SION1 sets the width ${\displaystyle \sigma _{\text{atom}}}$ 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 ${\displaystyle \mathrm {\AA} }$.