Developing the random phase approximation into a practical post-Kohn-Sham correlation model.

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Materials Science

Background:

• The random phase approximation (RPA) offers improved accuracy for density functional correlation energy.
• Previous RPA implementations were computationally prohibitive for routine use.

Purpose of the Study:

• To develop a computationally tractable reformulation of the RPA correlation model.
• To enable widespread application of RPA in electronic structure calculations.

Main Methods:

• Reformulated RPA correlation energy as a difference of electronic excitation energies.
• Expressed RPA correlation energy as an explicit functional of Kohn-Sham orbitals.
• Developed a stable algorithm using Newton-Schulz iteration to compute the response operator's sign function.

Main Results:

• The reformulated RPA significantly reduces computational complexity.
• The method achieves a computational scaling of O(N^5), comparable to MP2.
• The approach provides a robust and efficient zero-order post-Kohn-Sham correlation model.

Conclusions:

• The developed RPA method overcomes previous computational barriers.
• This advancement makes RPA a practical tool for accurate electronic structure predictions.
• The findings pave the way for more reliable computational chemistry and materials science.