The DOI matches its Crossref record; 32 of the 33 references it cites were found in a registry or an index.
Benchmarking a trapped-ion quantum computer with 30 qubits
Open accessAbstract
Quantum computers are rapidly becoming more capable, with dramatic increases in both qubit count \cite{kim2023evidence} and quality \cite{moses2023race}. Among different hardware approaches, trapped-ion quantum processors are a leading technology for quantum computing, with established high-fidelity operations and architectures with promising scaling. Here, we demonstrate and thoroughly benchmark the IonQ Forte system: configured as a single-chain 30-qubit trapped-ion quantum computer with all-to-all operations. We assess the performance of our quantum computer operation at the component level via direct randomized benchmarking (DRB) across all 30 choose 2 = 435 gate pairs. We then show the results of application-oriented \cite{IonQ_AQ20_2022}\cite{qedcPeerReviewed} benchmarks and show that the system passes the suite of algorithmic qubit (AQ) benchmarks up to #AQ 29. Finally, we use our component-level benchmarking to build a system-level model to predict the application benchmarking data through direct simulation. While we find that the system-level model correlates with the experiment in predicting application circuit performance, we note quantitative discrepancies indicating significant out-of-model errors, leading to higher predicted performance than what is observed. This highlights that as quantum computers move toward larger and higher-quality devices, characterization becomes more challenging, suggesting future work required to push performance further.
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“However, mobile qubit architectures, such as QCCD and optical tweezers24,25, can distribute resources more efficiently than stationary qubit architectures26–28, because qubits flow through the QPU like bits in a classical processor, with separated memory structures, data buses and logic units, each optimized for their purpose12.”
From A 98-qubit trapped-ion quantum computer with all-to-all connectivity (2026) · cites this paper as [28]
Citations
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Research works printed but not linked: 5
- Rui-Rui Li, Yi-Long Chen, Ran He, Shu-Qian Chen, Wen-Hao Qi, Jin-Ming Cui, Yun-Feng Huang, Chuan-Feng Li, and Guang-Can Guo. ``A low-crosstalk double-side addressing system using acousto-optic deflectors for atomic ion qubits'' (2023). arXiv:2306.01307. · arXiv
- Andrii Maksymov, Jason Nguyen, Yunseong Nam, and Igor Markov. ``Enhancing quantum computer performance via symmetrization'' (2023). arXiv:2301.07233. · arXiv
- Anthony M. Polloreno, Arnaud Carignan-Dugas, Jordan Hines, Robin Blume-Kohout, Kevin Young, and Timothy Proctor. ``A theory of direct randomized benchmarking'' (2023). arXiv:2302.13853. · arXiv
- Sergei V. Isakov, Dvir Kafri, Orion Martin, Catherine Vollgraff Heidweiller, Wojciech Mruczkiewicz, Matthew P. Harrigan, Nicholas C. Rubin, Ross Thomson, Michael Broughton, Kevin Kissell, Evan Peters, Erik Gustafson, Andy C. Y Li, Henry Lamm, Gabriel Perdue, Alan K. Ho, Doug Strain, and Sergio Boixo. ``Simulations of quantum circuits with approximate noise using qsim and cirq'' (2021). arXiv:2111.02396. · arXiv
- David C McKay, Ian Hincks, Emily J Pritchett, Malcolm Carroll, Luke CG Govia, and Seth T Merkel. ``Benchmarking quantum processor performance at scale'' (2023). arXiv:2311.05933. · arXiv
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Proctor, T. J., Young, K. C., Baczewski, A., & Blume-Kohout, R. (2025) · Nature Reviews Physics · doi:10.1038/s42254-024-00796-z · Cited by 116
Quantum simulation of spin-boson models with structured bath
Sun, K., Kang, M., Nuomin, H., Schwartz, G., Beratan, D. N., Brown, K. R., & Kim, J. (2025) · Nature Communications · doi:10.1038/s41467-025-59296-y · Cited by 41
Roadmap on quantum thermodynamics
Campbell, S., D’Amico, I., Ciampini, M. A., Anders, J., Ares, N., Artini, S., Auffèves, A., Oftelie, L. B., Bettmann, L. P., Bonança, M. V. S., et al. (2025) · Quantum Science and Technology · doi:10.1088/2058-9565/ae1e27 · Cited by 83
Kang, M., Nuomin, H., Chowdhury, S. N., Yuly, J. L., Sun, K., Whitlow, J., Valdiviezo, J., Zhang, Z., Zhang, P., Beratan, D. N., et al. (2024) · Nature Reviews Chemistry · doi:10.1038/s41570-024-00595-1 · Cited by 40
Metadata
- Authors
- Chen, J.-S., Nielsen, E., Ebert, M., Inlek, V., Wright, K., Chaplin, V., Maksymov, A., Páez, E., Poudel, A., Maunz, P., & Gamble, J.
- Affiliations
- IonQ (United States) (US)
- IonQ, College Park, MD 20740
- ORCID
- Venue
- Quantum
- Published
- 2024-11-07
- Volume
- 8
- Pages
- 1516
- ISSN
- 2521-327X (ISSN-L)
- OpenAlex
- W4404140215
- Cited by
- 103
- References
- 33
- Citations by year
- 2026: 39 · 2025: 56 · 2024: 7
- FWCI
- 15.11
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Quantum (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (acceptedVersion)
- arXiv (Cornell University) (submittedVersion, cc-by-nc-sa)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Information and Cryptography
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Mechanics and Applications
- Keywords
- trapped-ion quantum computer, quantum hardware characterization
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