Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure

Schmerwitz YL, Thirion L, Levi G, Jónsson EÖ, Bilous P, Jónsson H, Hansmann P (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Journal of Chemical Theory and Computation American Chemical Society

DOI: 10.1021/acs.jctc.4c01479

Abstract

By combining Hartree-Fock with a neural-network-supported quantum-cluster solver proposed recently in the context of solid-state lattice models, we formulate a scheme for selective neural-network configuration interaction (NNCI) calculations and implement it with various options for the type of basis set and boundary conditions. The method’s performance is evaluated in studies of several small molecules as a step toward calculations of larger systems. In particular, the correlation energy in the N2 molecule is compared with published full CI calculations that included nearly 1010 Slater determinants, and the results are reproduced with only 4 × 105 determinants using NNCI. A clear advantage is seen from increasing the set of orbitals included rather than approaching full CI for a smaller set. The method’s high efficiency and implementation in a condensed matter simulation software expands the applicability of CI calculations to a wider range of problems, even extended systems through an embedding approach.

Involved external institutions

University of Iceland (UI) / Háskóli Íslands IS Iceland (IS) Max-Planck-Institut für die Physik des Lichts (MPL) / Max Planck Institute for the Science of Light DE Germany (DE)

How to cite

APA:

Schmerwitz, Y.L., Thirion, L., Levi, G., Jónsson, E.Ö., Bilous, P., Jónsson, H., & Hansmann, P. (2025). Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure. Journal of Chemical Theory and Computation. https://doi.org/10.1021/acs.jctc.4c01479

MLA:

Schmerwitz, Yorick L.A., et al. "Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure." Journal of Chemical Theory and Computation (2025).

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