Efficient Electronic Structure Theory via Hierarchical Scale-Adaptive Coupled-Cluster Formalism: I. Theory and Computational Complexity Analysis

TL;DR

This paper introduces a hierarchical, scale-adaptive coupled-cluster method that significantly reduces computational complexity and storage requirements for electronic structure calculations by leveraging tensor hierarchies and approximation techniques.

Contribution

It develops a novel reduced-scaling coupled-cluster formalism using hierarchical tensor representations and scale-adaptive algebra, enabling efficient evaluation of many-body interactions.

Findings

Storage requirement reduced to O(N)

Evaluation of coupled-cluster diagrams in O(N log N)

Further complexity reduction for higher-order equations

Abstract

A novel reduced-scaling, general-order coupled-cluster approach is formulated by exploiting hierarchical representations of many-body tensors, combined with the recently suggested formalism of scale-adaptive tensor algebra. Inspired by the hierarchical techniques from the renormalization group approach, H/H2-matrix algebra and fast multipole method, the computational scaling reduction in our formalism is achieved via coarsening of quantum many-body interactions at larger interaction scales, thus imposing a hierarchical structure on many-body tensors of coupled-cluster theory. In our approach, the interaction scale can be defined on any appropriate Euclidean domain (spatial domain, momentum-space domain, energy domain, etc.). We show that the hierarchically resolved many-body tensors reduce the storage requirements to O(N), where N is the number of simulated quantum particles. Subsequently, we prove that any connected many-body diagram with arbitrary-order tensors, e.g., an arbitrary coupled-cluster diagram, can be evaluated in O(NlogN) floating-point operations. On top of that, we elaborate an additional approximation to further reduce the computational complexity of higher-order coupled-cluster equations, i.e., equations involving higher than double excitations, which otherwise would introduce a large prefactor into formal O(NlogN) scaling.