Accuracy and Resource Estimations for Quantum Chemistry on a Near-Term Quantum Computer

• Published in: Journal of chemical theory and computation Vol. 15; no. 9; pp. 4764 - 4780
• Main Authors: Kühn, Michael, Zanker, Sebastian, Deglmann, Peter, Marthaler, Michael, Weiß, Horst
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 10.09.2019
• Subjects: Algorithms; Chemical reactions; Clusters; Coupling (molecular); Density functional theory; Electronic structure; Organic chemistry; Quantum chemistry; Quantum computers; Quantum computing; Qubits (quantum computing)
• ISSN: 1549-9618; 1549-9626; 1549-9626
• DOI: 10.1021/acs.jctc.9b00236

One of the most important application areas of molecular quantum chemistry is the study and prediction of chemical reactivity. Large-scale, fully error-tolerant quantum computers could provide exact or near-exact solutions to the underlying electronic structure problem with exponentially less effort than a classical computer thus enabling highly accurate predictions for comparably large molecular systems. In the nearer future, however, only “noisy” devices with a limited number of qubits that are subject to decoherence will be available. For such near-term quantum computers the hybrid quantum-classical variational quantum eigensolver algorithm in combination with the unitary coupled-cluster ansatz (UCCSD-VQE) [Peruzzo et al. Nat. Commun. 2014, 5, 4213 and McClean et al. New J. Phys. 2016, 18, 023023 ] has become an intensively discussed approach that could provide accurate results before the dawn of error-tolerant quantum computing. In this work we present an implementation of UCCSD-VQE that allows for the first time to treat both open- and closed-shell molecules. We study the accuracy of the obtained energies for nine small molecular systems as well as for four exemplary chemical reactions by comparing to well-established electronic structure methods like (nonunitary) coupled-cluster and density functional theory. Finally, we roughly estimate the required quantum hardware resources to obtain “useful” results for practical purposes.