Category:Constrained-random-phase approximation: Difference between revisions
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The target space is usually low-dimensional and therefore allows for the application of a higher level theory, such as dynamical mean field theory. | The target space is usually low-dimensional and therefore allows for the application of a higher level theory, such as dynamical mean field theory. | ||
More information about CRPA is found on following page: | More information about CRPA is found on the following page: | ||
[[Constrained–random-phase–approximation_formalism]] | [[Constrained–random-phase–approximation_formalism]] | ||
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[[Category:VASP|ACFDT]][[Category:Many- | [[Category:VASP|ACFDT]][[Category:Many-body perturbation theory]][[Category:VASP6]] | ||
Revision as of 10:30, 19 July 2022
All tags and articles that deal with CRPA calculations are members of this category.
Theoretical Background
The constrained random-phase approximation (CRPA) is a method that allows to calculate the effective interaction parameter U, J and J' for model Hamiltonians. The main idea is to neglect screening effects of specific target states in the screened Coulomb interaction W of the GW method. The resulting partially screened Coulomb interaction is usually evaluated in a localized basis that spans the target space and is described by the model Hamiltonian. The target space is usually low-dimensional and therefore allows for the application of a higher level theory, such as dynamical mean field theory.
More information about CRPA is found on the following page:
Constrained–random-phase–approximation_formalism
How to
Pages in category "Constrained-random-phase approximation"
The following 7 pages are in this category, out of 7 total.