Accurate Helium-Benzene Potential: from CCSD(T) to Gaussian Process Regression
Shahzad Akram, Sutirtha Paul, Collin Kovacs, Vasileios Maroulas, Adrian Del Maestro, Konstantinos D. Vogiatzis

TL;DR
This paper develops a highly accurate potential energy surface for helium-benzene interactions using advanced quantum chemistry and Gaussian process regression, enabling improved simulations of helium on aromatic systems.
Contribution
It introduces a benchmark PES combining CCSD(T) and Gaussian process regression, advancing modeling of weakly bound helium-graphene systems.
Findings
PES achieves sub-cm-1 accuracy.
PIMC simulations show different solvation behavior compared to Lennard-Jones models.
Benchmark energies and physical component analysis validate the approach.
Abstract
The accurate modeling of non-covalent interactions between helium and graphitic materials is important for understanding quantum phenomena in reduced dimensions, with the helium-benzene complex serving as the fundamental prototype. However, creating a quantitatively reliable potential energy surface (PES) for this weakly bound system remains a significant computational challenge. In this work, we present a comprehensive, multi-level investigation of the He-Bz interaction, establishing benchmark energies using high-level coupled-cluster singles-and-doubles with perturbative triples (CCSD(T)) methods extrapolated to the complete basis set limit and assessing higher-order (CCSDT(Q)) contributions. We use symmetry-adapted perturbation theory (SAPT) to benchmark it against CCSD(T) and to decompose the interaction into its physical components-confirming it is dominated by a balance between…
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Taxonomy
TopicsQuantum, superfluid, helium dynamics · Hydrogen Storage and Materials · Inorganic Fluorides and Related Compounds
