Category:Low-scaling GW and RPA: Difference between revisions

This category shows all tags and articles concerning low scaling GW and RPA algorithms available as of VASP.6 and newer.

Theoretical Background

The computational cost of diagrammatic methods typically exceeds the one of hybrid DFT calculations, since a frequency dependent Hamiltonian is diagonalized. Conventional GW and RPA/ACFDT algorithms typically scale with the forth power of the system size and are, thus, limited to relatively small system sizes. However, by performing all calculations on the imaginary time and imaginary frequency axis one can exploit coarse Fourier transformation compatible grids and obtain a cubic scaling GW and RPA/ACFDT algorithm. These algorithms can be used to study relatively large systems with diagrammatic methods.

How to

• A practical guide to low-scaling GW calculations can be found here.