ML LCOUPLE: Difference between revisions
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<math> | <math> | ||
\delta \mu = \int\limits_{0}^{1} \langle \frac{dH(\lambda)}{d\lambda} \rangle_{\lambda} d\lambda. | \delta \mu = \int\limits_{0}^{1} \langle \frac{dH(\lambda)}{d\lambda} \rangle_{\lambda} d\lambda. | ||
</math> | |||
Using machine learning force fields the Hamiltonian can be written as | |||
<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}}. | |||
</math> | </math> | ||
Revision as of 14:59, 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
Failed to parse (unknown function "\lambd"): {\displaystyle 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}}. }
Related Tags and Sections
ML_FF_LMLFF, ML_FF_NATOM_COUPLED_MB, ML_FF_ICOUPLE_MB, ML_FF_RCOUPLE_MB