Solving an industrially relevant quantum chemistry problem on quantum hardware

Abstract Quantum chemical calculations are among the most promising applications for quantum computing. Implementations of dedicated quantum algorithms on available quantum hardware were so far, however, mostly limited to comparatively simple systems without strong correlations. As such, they can also be addressed by classically efficient single-reference methods. Here we calculate the lowest energy eigenvalue of active space Hamiltonians of industrially relevant and strongly correlated metal chelates on trapped ion quantum hardware, and integrate the results into a typical industrial quantum chemical workflow to arrive at chemically meaningful properties. We are able to achieve chemical accuracy by training a variational quantum algorithm on quantum hardware, followed by a classical diagonalization in the subspace of states measured as outputs of the quantum circuit. This approach is particularly measurement-efficient, requiring 600 single-shot measurements per cost function evaluation on a ten qubit system, and allows for efficient post-processing to handle erroneous runs.

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Publication Details

Journal
Quantum Science and Technology
Published
2024-12-13
DOI
https://doi.org/10.1088/2058-9565/ad9ed3
Citations
6
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
2.08

Funders

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article

Solving an industrially relevant quantum chemistry problem on quantum hardware

Robert S. Freund, Stefan Wolf, Ludwig Nützel, Nina Stockinger et al.
6 citations
Quantum Science and Technology
Quantum Computing Algorithms and Architecture
2.08
article

Solving an industrially relevant quantum chemistry problem on quantum hardware

Robert S. Freund, Stefan Wolf, Ludwig Nützel, Nina Stockinger, Christian D. Marciniak, Alex Steiner, Alexander Gresch, Michael J. Hartmann, Thomas Monz, Timo Eckstein, Michael Kühn, Lucas Marti, Lukas Hehn
article en
6 citations

Abstract

Abstract Quantum chemical calculations are among the most promising applications for quantum computing. Implementations of dedicated quantum algorithms on available quantum hardware were so far, however, mostly limited to comparatively simple systems without strong correlations. As such, they can also be addressed by classically efficient single-reference methods. Here we calculate the lowest energy eigenvalue of active space Hamiltonians of industrially relevant and strongly correlated metal chelates on trapped ion quantum hardware, and integrate the results into a typical industrial quantum chemical workflow to arrive at chemically meaningful properties. We are able to achieve chemical accuracy by training a variational quantum algorithm on quantum hardware, followed by a classical diagonalization in the subspace of states measured as outputs of the quantum circuit. This approach is particularly measurement-efficient, requiring 600 single-shot measurements per cost function evaluation on a ten qubit system, and allows for efficient post-processing to handle erroneous runs.

Quantum Science and TechnologyVol. 10(1)
Universität Hamburg (DE), Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Universität Innsbruck (AT), BASF (Germany) (DE), Max Planck Institute for the Science of Light (DE), Heinrich Heine University Düsseldorf (DE), Technical University of Munich (DE), Hamburg University of Technology (DE)
Bundesministerium für Bildung und Forschung, Austrian Science Fund, Österreichische Forschungsförderungsgesellschaft, European Research Council, HORIZON EUROPE European Innovation Council
Affordable and clean energy
Openalex Percentile: Top 11%
Quantum Computing Algorithms and Architecture
2.08
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