ML MRB1: Difference between revisions

Revision as of 07:40, 8 June 2021

ML_FF_MRB1_MB = [integer]
Default: ML_FF_MRB1_MB = NINT(ML_FF_RCUT1_MB/ML_FF_SION1_MB*1.5)

Description: This tag sets the number of radial basis sets used to expand the atomic distribution for the radial descriptor within the machine learning force field method.

The values for ML_FF_MRB1_MB and ML_FF_MRB2_MB are automatically set by the code (empirically) and usually need not to be set by the user. Only in very few cases if the error in the radial expansion (see later in the text) is not sufficiently low these values need to be adjusted manually.

The tags ML_FF_MRB1_MB and ML_FF_MRB2_MB set the number of radial basis sets used to expand the atomic distribution of the radial and angular density. These tags depend very sensitively on the cut-off radius of the descriptor (ML_FF_RCUT1_MB and ML_FF_RCUT2_MB) and the width of the Gaussian functions used in the broadening of the atomic distributions (ML_FF_SION1_MB and ML_FF_SION2_MB). The error occuring due to the expansion of the radial basis functions is monitored in the ML_LOGFILE file by searching for the following line "Error in radial expansion: ...". A typical reasonable value for the error threshold that was empirically determined (by us and in reference ^[1]) is $\pm 0.02$ . Hence, the number of basis functions should be adjusted until the error written in the ML_LOGFILE is smaller than this value. A more detailed description of the basis sets is given in appendix A of reference ^[2].

References

Related Tags and Sections

ML_FF_LMLFF, ML_FF_MRB2_MB, ML_FF_W1_MB, ML_FF_RCUT1_MB, ML_FF_RCUT2_MB, ML_FF_SION1_MB, ML_FF_SION2_MB

Examples that use this tag

[szlachta:prb:2014-1] W. J. Szlachta, A. P. Bartók, and G. Csányi, Phys. Rev. B 90, 104108 (2014).

[jinnouchi2:arx:2019-2] R. Jinnouchi, F. Karsai, and G. Kresse, Phys. Rev. B 100, 014105 (2019).

[1]

[2]

@@ Line 3: / Line 3: @@
 Description: This tag sets the number of radial basis sets used to expand the atomic distribution for the radial descriptor within the machine learning force field method.
 ----
+The values for {{TAG|ML_FF_MRB1_MB}} and {{TAG|ML_FF_MRB2_MB}} are automatically set by the code (empirically) and usually need not to be set by the user. Only in very few cases if the error in the radial expansion (see later in the text) is not sufficiently low these values need to be adjusted manually.
+The tags {{TAG|ML_FF_MRB1_MB}} and {{TAG|ML_FF_MRB2_MB}} set the number of radial basis sets used to expand the atomic distribution of the radial and angular density. These tags depend very sensitively on the cut-off radius of the descriptor ({{TAG|ML_FF_RCUT1_MB}} and {{TAG|ML_FF_RCUT2_MB}}) and the width of the Gaussian functions used in the broadening of the atomic distributions ({{TAG|ML_FF_SION1_MB}} and {{TAG|ML_FF_SION2_MB}}). The error occuring due to the expansion of the radial basis functions is monitored in the {{TAG|ML_LOGFILE}} file by searching for the following line "''Error in radial expansion: ...''". A typical reasonable value for the error threshold that was empirically determined (by us and in reference {{cite|szlachta:prb:2014}}) is <math>\pm 0.02</math>. Hence, the number of basis functions should be adjusted until the error written in the {{TAG|ML_LOGFILE}} is smaller than this value. A more detailed description of the basis sets is given in appendix A of reference {{cite|jinnouchi2:arx:2019}}.
-The value of {{TAG|ML_FF_MRB1_MB}} depends on the choice of the cut-off radius ({{TAG|ML_FF_RCUT1_MB}} and the width of the Gaussian functions used in the broadening of the atomic distributions {{TAG|ML_FF_SION1_MB}}. The error of the basis calculated on a predetermined grid is calculated on the beginning of the calculations (for details see reference {{cite|jinnouchi2:arx:2019}}).
 == References ==