Random phase approximation-based local natural orbital coupled cluster theory

TL;DR

This paper introduces RPA as an effective low-level theory alternative to MP2 within the LNO-CC framework, improving convergence especially for metallic systems.

Contribution

The study demonstrates that RPA-based LNO-CC performs comparably to MP2-based methods for insulators and converges faster for metals, offering a new approach for local correlation calculations.

Findings

RPA-based LNO-CC matches MP2 performance for systems with large energy gaps.

RPA-based LNO-CC converges faster to the canonical limit in metallic systems.

RPA is identified as a promising alternative to MP2 in local correlation methods.

Abstract

Practical applications of fragment embedding and closely related local correlation methods critically depend on a judicious choice of a low-level theory to define the local embedding subspace and to capture long-range electrostatic and correlation effects outside the embedding region. Second-order M{\o}ller-Plesset perturbation theory (MP2) is by far the most widely used correlated low-level theory; however, its applicability becomes questionable in systems where MP2 is known to fail either quantitatively or qualitatively. In this work, we present the random phase approximation (RPA) as a promising alternative low-level theory to MP2 within the local natural orbital-based coupled-cluster (LNO-CC) framework. We demonstrate that RPA-based LNO-CC closely matches the performance of its MP2-based counterpart for systems with sizable energy gaps, while delivering significantly faster convergence toward the canonical coupled-cluster limit for metallic systems, particularly as the thermodynamic limit is approached. These results highlight the critical role of the low-level theory in fragment embedding and local correlation methods and identify RPA as a compelling alternative to the commonly used MP2.