Stochastically accelerated perturbative triples correction in coupled cluster calculations

TL;DR

This paper presents a semi-stochastic algorithm for the perturbative triples correction in coupled-cluster calculations, significantly reducing computational effort while maintaining accuracy, enabling studies of larger molecular systems.

Contribution

It introduces a novel semi-stochastic method that balances accuracy and efficiency in coupled-cluster perturbative triples correction calculations.

Findings

Achieves 0.5 millihartree precision with only 10% of full computational effort.

Provides unbiased estimates with statistical errors decreasing as calculations proceed.

Enables efficient and accurate computations for complex molecular systems.

Abstract

We introduce a novel algorithm that leverages stochastic sampling techniques to compute the perturbative triples correction in the coupled-cluster (CC) framework. By combining elements of randomness and determinism, our algorithm achieves a favorable balance between accuracy and computational cost. The main advantage of this algorithm is that it allows for the calculation to be stopped at any time, providing an unbiased estimate, with a statistical error that goes to zero as the exact calculation is approached. We provide evidence that our semi-stochastic algorithm achieves substantial computational savings compared to traditional deterministic methods. Specifically, we demonstrate that a precision of 0.5 millihartree can be attained with only 10\% of the computational effort required by the full calculation. This work opens up new avenues for efficient and accurate computations, enabling investigations of complex molecular systems that were previously computationally prohibitive.