Stochastic tensor contraction for quantum chemistry

TL;DR

This paper introduces stochastic tensor contraction to significantly reduce computational costs in quantum chemistry calculations, enabling more efficient and scalable simulations.

Contribution

The authors develop a stochastic tensor contraction method applied to coupled cluster theory, achieving reduced scaling and improved efficiency over existing approaches.

Findings

Reduced computational scaling to mean-field level for high-accuracy energy calculations

Achieved an order-of-magnitude speedup compared to local correlation methods

Demonstrated robustness against system size and electron delocalization effects

Abstract

Many computational methods in ab initio quantum chemistry are formulated in terms of high-order tensor contractions, whose cost determines the size of system that can be studied. We introduce stochastic tensor contraction to perform such operations with greatly reduced cost, and present its application to the gold-standard quantum chemistry method, coupled cluster theory with up to perturbative triples. For total energy errors more stringent than chemical accuracy, we reduce the computational scaling to that of mean-field theory, while starting to approach the mean-field absolute cost, thereby challenging the existing cost-to-accuracy landscape. Benchmarks against state-of-the-art local correlation approximations further show that we achieve an order-of-magnitude improvement in both total computation time and error, with significantly reduced sensitivity to system dimensionality and electron delocalization. We conclude that stochastic tensor contraction is a powerful computational primitive to accelerate a wide range of quantum chemistry.