The distinguishable cluster approximation

TL;DR

The paper introduces the distinguishable cluster approximation, a novel method derived from CCSD that accurately models strongly correlated states and dissociation processes with manageable computational cost.

Contribution

It presents a new particle distinguishability-based modification of CCSD that improves accuracy for strongly correlated systems and dissociation scenarios.

Findings

Outperforms CCSD near equilibrium geometries.

Accurately describes dissociation of molecules like N2.

Treats fully dissociated systems exactly.

Abstract

A new method that accurately describes strongly correlated states and captures dynamical correlation is presented. It is derived as a modification of coupled-cluster theory with single and double excitations (CCSD) through consideration of particle distinguishability between dissociated fragments, whilst retaining the key desirable properties of particle-hole symmetry, size extensivity, invariance to rotations within the occupied and virtual spaces, and exactness for two-electron subsystems. The resulting method called the distinguishable cluster approximation, smoothly dissociates difficult cases such as the nitrogen molecule, with the modest N^6 computational cost of CCSD. Even for molecules near their equilibrium geometries, the new model outperforms CCSD. It also accurately describes the massively correlated states encountered when dissociating hydrogen lattices, a proxy for the metal-insulator transition, and the fully dissociated system is treated exactly.