Random-phase approximation and its applications in computational chemistry and materials science

TL;DR

This paper reviews the random-phase approximation (RPA) in computational chemistry and materials science, discussing its theory, applications, computational cost, and future development directions.

Contribution

It provides a comprehensive overview of RPA's theoretical formulations, practical applications, and discusses correction schemes and computational challenges.

Findings

RPA effectively computes electronic correlation energies.

Applications demonstrate RPA's relevance in realistic systems.

Discussion of correction schemes enhances RPA's accuracy.

Abstract

The random-phase approximation (RPA) as an approach for computing the electronic correlation energy is reviewed. After a brief account of its basic concept and historical development, the paper is devoted to the theoretical formulations of RPA, and its applications to realistic systems. With several illustrating applications, we discuss the implications of RPA for computational chemistry and materials science. The computational cost of RPA is also addressed which is critical for its widespread use in future applications. In addition, current correction schemes going beyond RPA and directions of further development will be discussed.