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arXiv:2510.12887

Many-body post-processing of density functional calculations using the variational quantum eigensolver for Bader charge analysis

Erik Schultheis, Alexander Rehn, Gabriel Breuil

Published Oct 14, 2025• 0 citations
arXivHTMLPDF

Abstract

Quantum chemistry and condensed matter physics are among the most promising applications of quantum computers. Further, estimating properties of a material is crucial to evaluate its industrial applications. To investigate charge distributions of weakly and strongly correlated systems we calculate Bader charges for various periodic systems by solving many-body Hamiltonians using the variational quantum eigensolver. The Hamiltonians are computed from Kohn-Sham orbitals obtained from a prior DFT calculation. We first demonstrate the accuracy of our method on various doped MgH2 supercells. Further, we show that our approach, compared to standard DFT, significantly improves the Bader charge values for strongly correlated transition metal oxides, where we take DFT+U results as a reference. The computational framework behind our many-body calculations, called Dopyqo, is made openly available as a software package.

DOI
10.48550/arxiv.2510.12887

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Quantum chemistry and condensed matter physics are among the most promising applications of quantum computers. Further, estimating properties of a material is crucial to evaluate its industrial applications. To investigate charge distributions of weakly and strongly correlated systems we calculate Bader charges for various periodic systems by solving many-body Hamiltonians using the variational quantum eigensolver. The Hamiltonians are computed from Kohn-Sham orbitals obtained from a prior DFT calculation. We first demonstrate the accuracy of our method on various doped MgH2 supercells. Further, we show that our approach, compared to standard DFT, significantly improves the Bader charge values for strongly correlated transition metal oxides, where we take DFT+U results as a reference. The computational framework behind our many-body calculations, called Dopyqo, is made openly available as a software package.
Quantum chemistry and condensed matter physics are among the most promising applications of quantum computers. Further, estimating properties of materials is crucial to evaluate their industrial applications. Dopyqo bridges the gap between DFT and many-body simulations of periodic systems by building many-body Hamiltonians and solving them using classical and quantum algorithms. The Hamiltonians are computed from Kohn-Sham orbitals obtained from a prior Quantum ESPRESSO2 DFT calculation. We present the usefulness of Dopyqo by performing geometry optimization and calculating partial atomic charges for strongly correlated systems and comparing them to DFT and DFT+U.
Dopyqo bridges the gap between DFT and many-body simulations of periodic systems by building many-body Hamiltonians and providing tools for solving them using classical and quantum algorithms. The Hamiltonians are computed from Kohn-Sham orbitals obtained from a prior Quantum ESPRESSO DFT calculation. The calculated Hamiltonians can be used in conjunction with any other quantum computing framework or algorithm. We present the usefulness of Dopyqo on its own by performing geometry optimization and calculating partial atomic charges for strongly correlated systems and comparing them to DFT and DFT+U.
Quantum computing has emerged as a promising platform for simulating strongly correlated systems in chemistry, for which the standard quantum chemistry methods are either qualitatively inaccurate or too expensive. However, due to the hardware limitations of the available noisy near-term quantum devices, their application is currently limited only to small chemical systems. One way for extending the range of applicability can be achieved within the quantum embedding approach. Herein, we employ the projection-based embedding method for combining the variational quantum eigensolver (VQE) algorithm, although not limited to, with density functional theory (DFT). The developed VQE-in-DFT method is then implemented efficiently on a real quantum device and employed for simulating the triple bond breaking process in butyronitrile. The results presented herein show that the developed method is a promising approach for simulating systems with a strongly correlated fragment on a quantum computer.
Abstract This article is a short introduction to the modern computational techniques used to tackle the many-body problem in materials. The aim is to present the basic ideas, using simple examples to illustrate strengths and weaknesses of each method. We will start from density-functional theory (DFT) and the Kohn–Sham construction—the standard computational tools for performing electronic structure calculations. Leaving the realm of rigorous density-functional theory, we will discuss the established practice of adopting the Kohn–Sham Hamiltonian as approximate model. After recalling the triumphs of the Kohn–Sham description, we will stress the fundamental reasons of its failure for strongly-correlated compounds, and discuss the strategies adopted to overcome the problem. The article will then focus on the most effective method so far, the DFT+DMFT technique and its extensions. Achievements, open issues and possible future developments will be reviewed. The key differences between dynamical (DFT+DMFT) and static (DFT+ U ) mean-field methods will be elucidated. In the conclusion, we will assess the apparent dichotomy between first-principles and model-based techniques, emphasizing the common ground that in fact they share.
Quantum computers open up new avenues for modelling the physical properties of materials and molecules. Density Functional Theory (DFT) is the gold standard classical algorithm for predicting these properties, but relies on approximations of the unknown universal functional, limiting its general applicability for many fundamental and technologically relevant systems. In this work we develop a hybrid quantum/classical algorithm called quantum enhanced DFT (QEDFT) that systematically constructs quantum approximations of the universal functional using data obtained from a quantum computer. We benchmark the QEDFT algorithm on the Fermi-Hubbard model, both numerically and on data from experiments on real quantum hardware. We find that QEDFT surpasses the quality of groundstate results obtained from Hartree-Fock DFT, as well as from direct application of conventional quantum algorithms such as VQE. Furthermore, we demonstrate that QEDFT works even when only noisy, low-depth quantum computation is available, by benchmarking the algorithm on data obtained from Google's quantum computer. We further show how QEDFT also captures quintessential properties of strongly correlated Mott physics for large Fermi-Hubbard systems using functionals generated on much smaller system sizes. Our results indicate that QEDFT can be applied to realistic materials and molecular systems, and has the potential to outperform the direct application of either DFT or VQE alone, without the requirement of large scale or fully fault-tolerant quantum computers.
A generating coordinate is introduced into the exchange-correlation functional of density functional theory (DFT). The many-body wave function is represented as a superposition of Kohn–Sham (KS) Slater determinants arising from different values of the generating coordinate. This superposition is used to variationally calculate many-body energies and wave functions from solutions of the KS equation of DFT. The method works for ground and excited states, and does not depend on identifying the KS orbitals and energies with physical ones. Numerical application to the Helium isoelectronic series illustrates the method’s viability and potential.