Cubic scaling algorithms for RPA correlation using interpolative separable density fitting
dc.contributor.author | Lu, J | |
dc.contributor.author | Thicke, K | |
dc.date.accessioned | 2017-04-23T15:30:46Z | |
dc.date.available | 2017-04-23T15:30:46Z | |
dc.date.issued | 2017-04-23 | |
dc.description.abstract | We present a new cubic scaling algorithm for the calculation of the RPA correlation energy. Our scheme splits up the dependence between the occupied and virtual orbitals in $\chi^0$ by use of Cauchy's integral formula. This introduces an additional integral to be carried out, for which we provide a geometrically convergent quadrature rule. Our scheme also uses the newly developed Interpolative Separable Density Fitting algorithm to further reduce the computational cost in a way analogous to that of the Resolution of Identity method. | |
dc.format.extent | 21 pages, 6 figures | |
dc.identifier | ||
dc.identifier.uri | ||
dc.publisher | Elsevier BV | |
dc.subject | physics.comp-ph | |
dc.subject | physics.comp-ph | |
dc.subject | math.NA | |
dc.title | Cubic scaling algorithms for RPA correlation using interpolative separable density fitting | |
dc.type | Journal article | |
duke.contributor.orcid | Lu, J|0000-0001-6255-5165 | |
pubs.author-url | ||
pubs.organisational-group | Chemistry | |
pubs.organisational-group | Duke | |
pubs.organisational-group | Mathematics | |
pubs.organisational-group | Physics | |
pubs.organisational-group | Trinity College of Arts & Sciences |