Basis set truncation corrections for improved frozen natural orbital CCSD(T) energies

Abstract

A number of approaches are proposed and assessed to reduce the frozen natural orbital (FNO) truncation error of coupled-cluster singles and doubles with perturbative triples [CCSD(T)] energies. The diagrammatic energy decomposition method of Irmler and Grüneis [J. Chem. Phys. 151, 104107 (2019)] is extended to the FNO truncation correction of the particle-particle ladder (PPL) term in the case of closed- and open-shell molecular systems. The approach is tested for reaction, interaction, and atomization energies, and it is found the most robust for a wider range of FNO truncation thresholds outperforming the commonly employed additive MP2 correction. We also show that the linear extrapolation (LE) of FNO-CCSD(T) energies as a function of second-order Møller–Plesset (MP2) energies provides the best correlation energies and most balanced energy differences with tighter FNO thresholds, but it lacks systematic error compensation that would be required for the better performance with looser FNO thresholds. Further insight is gained from a diagrammatic and spin-component decomposition based analysis. Moreover, orbital (pair) specific energy decompositions are utilised to introduce size-consistent variants of the promising PPL and LE FNO corrections and their analogues for (T), which are also readily applicable in the context of popular local correlation methods.

GRAPHICAL ABSTRACT

Keywords:

• Frozen natural orbitals
• corrections for basis set truncation
• coupled-cluster theory
• CCSD(T)

Acknowledgments

This paper is dedicated to Professor John F. Stanton on the happy occasion of his 60th birthday. MK wishes to express his gratitude to John for the fruitful scientific collaborations and continuous support.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors are grateful for the financial support from the National Research, Development, and Innovation Office (NKFIH, Grant No. KKP126451). The research reported in this paper and carried out at BME has been supported by the NRDI Fund (TKP2020 IES, Grant No. BME-IE-BIO) based on the charter of bolster issued by the NRDI Office under the auspices of the Ministry for Innovation and Technology. The work of PRN is supported by the ÚNKP-20-5 New National Excellence Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation Fund and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences. The computing time granted on the Hungarian HPC Infrastructure at NIIF Institute, Hungary, and DECI resources Kay with support from the PRACE AISBL are gratefully acknowledged.