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Updated: Jun 11, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
Published on: April 8, 2020
Accelerating the convergence of coupled cluster calculations of the homogeneous electron gas using Bayesian ridge
Julie Butler1,2, Morten Hjorth-Jensen2,3, Justin G Lietz4
1Department of Biochemistry, Chemistry, and Physics, University of Mount Union, Alliance, Ohio 46601, USA.
Abstract:
The homogeneous electron gas is a system that has many applications in chemistry and physics. However, its infinite nature makes studies at the many-body level complicated due to long computational run times. Because it is size extensive, coupled cluster theory is capable of studying the homogeneous electron gas, but it still poses a large computational challenge as the time needed for precise calculations increases in a polynomial manner with the number of particles and single-particle states. Consequently, achieving convergence in energy calculations becomes challenging, if not prohibited, due to long computational run times and high computational resource requirements. This paper develops the sequential regression extrapolation (SRE) to predict the coupled cluster energies of the homogeneous electron gas in the complete basis limit using Bayesian ridge regression and many-body perturbation theory correlation energies to the second order to make predictions from calculations at truncated basis sizes. Using the SRE method, we were able to predict the coupled cluster double energies for the electron gas across a variety of values of N and rs, for a total of 70 predictions, with an average error of 5.20 × 10-4 hartree while saving 88.9 h of computational time. The SRE method can accurately extrapolate electron gas energies to the complete basis limit, saving both computational time and resources. Additionally, the SRE is a general method that can be applied to a variety of systems, many-body methods, and extrapolations.
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