Difference between revisions of "GAP theory"

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(Created page with "Gaussian approximation potentials (GAPs) are machine learning based interatomic potentials introduced by Albert Bartók and collaborators in 2010<ref name="bartok_2010" />. <...")
 
 
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<math>\bar{f}_* = \delta^2 \sum_t \alpha_t k(\textbf{d}_*, \textbf{d}_t) + f_0,</math>
 
<math>\bar{f}_* = \delta^2 \sum_t \alpha_t k(\textbf{d}_*, \textbf{d}_t) + f_0,</math>
 
== References ==
 
  
 
{{Reference list}}
 
{{Reference list}}

Latest revision as of 18:01, 19 July 2021

Gaussian approximation potentials (GAPs) are machine learning based interatomic potentials introduced by Albert Bartók and collaborators in 2010[1].

[math]\displaystyle{ \bar{f}_* = \delta^2 \sum_t \alpha_t k(\textbf{d}_*, \textbf{d}_t) + f_0, }[/math]

Reference list

  1. A.P. Bartók, M.C. Payne, R. Kondor, and G. Csányi. Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons. Phys. Rev. Lett. 104, 136403 (2010).