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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]
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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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