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Cited by 890

The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.

Quantum information processing with superconducting circuits: a review

Open access
Wendin, G·2017·Reports on Progress in Physics

Abstract

During the last ten years, superconducting circuits have passed from being interesting physical devices to becoming contenders for near-future useful and scalable quantum information processing (QIP). Advanced quantum simulation experiments have been shown with up to nine qubits, while a demonstration of quantum supremacy with fifty qubits is anticipated in just a few years. Quantum supremacy means that the quantum system can no longer be simulated by the most powerful classical supercomputers. Integrated classical-quantum computing systems are already emerging that can be used for software development and experimentation, even via web interfaces. Therefore, the time is ripe for describing some of the recent development of superconducting devices, systems and applications. As such, the discussion of superconducting qubits and circuits is limited to devices that are proven useful for current or near future applications. Consequently, the centre of interest is the practical applications of QIP, such as computation and simulation in Physics and Chemistry.

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Metadata

Authors
Wendin, G.
Venue
Reports on Progress in Physics
Published
2017-09-01
Volume
80
Issue
10
Pages
106001
ISSN
  • 0034-4885 (ISSN-L)
  • 1361-6633
OpenAlex
W2530095757
Cited by
890
References
88
FWCI
48.54
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Quantum information processing with superconducting circuits: a review. https://app.cochat.ai/papers/10.1088/1361-6633/aa7e1a
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Wendin, G. (2017). Quantum information processing with superconducting circuits: a review. Reports on Progress in Physics. https://doi.org/10.1088/1361-6633/aa7e1a

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.