4.7 Article

Benchmark tests and spin adaptation for the particle-particle random phase approximation

期刊

JOURNAL OF CHEMICAL PHYSICS
卷 139, 期 17, 页码 -

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AMER INST PHYSICS
DOI: 10.1063/1.4828728

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资金

  1. Office of Naval Research (ONR) [N00014-09-0576]
  2. National Science Foundation (NSF) [CHE-09-11119]
  3. Duke University
  4. FWO-Flanders (Scientific Research Fund Flanders)
  5. Swiss National Science Foundation (NSF(CH)) fellowship [PBELP2-143559]
  6. Swiss National Science Foundation (SNF) [PBELP2_143559] Funding Source: Swiss National Science Foundation (SNF)

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The particle-particle random phase approximation (pp-RPA) provides an approximation to the correlation energy in density functional theory via the adiabatic connection [H. van Aggelen, Y. Yang, and W. Yang, Phys. Rev. A 88, 030501 (2013)]. It has virtually no delocalization error nor static correlation error for single-bond systems. However, with its formal O(N-6) scaling, the pp-RPA is computationally expensive. In this paper, we implement a spin-separated and spin-adapted pp-RPA algorithm, which reduces the computational cost by a substantial factor. We then perform benchmark tests on the G2/97 enthalpies of formation database, DBH24 reaction barrier database, and four test sets for non-bonded interactions (HB6/04, CT7/04, DI6/04, and WI9/04). For the G2/97 database, the pp-RPA gives a significantly smaller mean absolute error (8.3 kcal/mol) than the direct particle-hole RPA (ph-RPA) (22.7 kcal/mol). Furthermore, the error in the pp-RPA is nearly constant with the number of atoms in a molecule, while the error in the ph-RPA increases. For chemical reactions involving typical organic closed-shell molecules, pp-and ph-RPA both give accurate reaction energies. Similarly, both RPAs perform well for reaction barriers and nonbonded interactions. These results suggest that the pp-RPA gives reliable energies in chemical applications. The adiabatic connection formalism based on pairing matrix fluctuation is therefore expected to lead to widely applicable and accurate density functionals. (C) 2013 AIP Publishing LLC.

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