English

Assessing the impact of nodal surface optimization in fixed-node diffusion Monte Carlo on non-covalent interactions

Chemical Physics 2026-04-07 v1 Strongly Correlated Electrons Computational Physics

Abstract

Diffusion quantum Monte Carlo (DMC) and coupled cluster theory [CCSD(T)] are widely-employed benchmark methods for noncovalent interactions (NCIs). However, recent studies have reported notable discrepancies across several hydrogen-bonded and dispersion-dominated systems, raising questions on the accuracy of the approximations underlying each approach. In DMC, the dominant error is expected to stem from the fixed-node approximation, where the nodal surface is typically taken from a single Slater determinant derived from a density functional theory or Hartree-Fock calculation. In this work, we assess the impact of nodal surface optimization on DMC predictions for 12 compounds spanning diverse NCIs, using a recently proposed antisymmetrized geminal power ansatz with natural orbitals. We find improved agreement with CCSD(T) for hydrogen-bonded systems, while having negligible effect for dispersion-dominated systems. These results provide a practical and computationally efficient route to resolving discrepancies in hydrogen-bonded interactions, while offering insight into the remaining differences in dispersion-dominated systems.

Keywords

Cite

@article{arxiv.2604.04329,
  title  = {Assessing the impact of nodal surface optimization in fixed-node diffusion Monte Carlo on non-covalent interactions},
  author = {Kousuke Nakano and Benjamin X. Shi and Dario Alfè and Andrea Zen},
  journal= {arXiv preprint arXiv:2604.04329},
  year   = {2026}
}

Comments

12 pages, 2 figures

R2 v1 2026-07-01T11:54:48.665Z