ML LCOUPLE: Difference between revisions

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<math>
H (\lambda) = \sum\limits_{i=1}^{N_{a}} \frac{|\mathbf{p}_{i}|^2}{2m_{i}} + \sum\limits_{i \notin M} U_{i}(\lambda) + \lambd \sum\limits_{i \in M} U_{i}(\lambda) + \sum\limits_{i}^{N_{a}} U_{i,\mathbf{atom}}.  
H (\lambda) = \sum\limits_{i=1}^{N_{a}} \frac{|\mathbf{p}_{i}|^2}{2m_{i}} + \sum\limits_{i \notin M} U_{i}(\lambda) + \lambda \sum\limits_{i \in M} U_{i}(\lambda) + \sum\limits_{i}^{N_{a}} U_{i,\mathbf{atom}}.  
</math>
</math>



Revision as of 15:00, 8 June 2021

ML_FF_LCOUPLE_MB = [logical]
Default: ML_FF_LCOUPLE_MB = .FALSE. 

Description: This tag specifies whether coupling parameters are used for the calculation of chemical potentials is used or not within the machine learning force field method.


In thermodynamic integration a coupling parameter is introduced to the Hamiltonian to smoothly switch between a "non-interacting" reference state and a "fully-interacting" state. The change of the free energy along this path is written as

Using machine learning force fields the Hamiltonian can be written as

Related Tags and Sections

ML_FF_LMLFF, ML_FF_NATOM_COUPLED_MB, ML_FF_ICOUPLE_MB, ML_FF_RCOUPLE_MB

Examples that use this tag