The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Procedure for systematically tuning up cross-talk in the cross-resonance gate
Open accessAbstract
We present improvements in both theoretical understanding and experimental implementation of the cross resonance (CR) gate that have led to shorter two-qubit gate times and interleaved randomized benchmarking fidelities exceeding 99%. The CR gate is an all-microwave two-qubit gate that does not require tunability and is therefore well suited to quantum computing architectures based on two-dimensional superconducting qubits. The performance of the gate has previously been hindered by long gate times and fidelities averaging 94--96%. We have developed a calibration procedure that accurately measures the full CR Hamiltonian. The resulting measurements agree with theoretical analysis of the gate and also elucidate the error terms that have previously limited gate fidelity. The increase in fidelity that we have achieved was accomplished by introducing a second microwave drive tone on the target qubit to cancel unwanted components of the CR Hamiltonian.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Superconducting quantum circuits at the surface code threshold for fault tolerance
Barends, R., Kelly, J., Megrant, A., Veitia, A., Sank, D., Jeffrey, E., White, T. C., Mutus, J., Fowler, A. G., Campbell, B., et al. (2014) · Nature · doi:10.1038/nature13171 · Cited by 1,733
Coherent Josephson Qubit Suitable for Scalable Quantum Integrated Circuits
Barends, R., Kelly, J., Megrant, A., Sank, D., Jeffrey, E., Chen, Y., Yin, Y., Chiaro, B., Mutus, J., Neill, C., et al. (2013) · Physical Review Letters · doi:10.1103/physrevlett.111.080502 · Cited by 779
Controlling the Spontaneous Emission of a Superconducting Transmon Qubit
Houck, A. A., Schreier, J. A., Johnson, B. R., Chow, J. M., Koch, J., Gambetta, J. M., Schuster, D. I., Frunzio, L., Devoret, M. H., Girvin, S. M., et al. (2008) · Physical Review Letters · doi:10.1103/physrevlett.101.080502 · Cited by 501
Self-citationCharacterizing quantum gates via randomized benchmarking
Magesan, E., Gambetta, J. M., & Emerson, J. (2012) · Physical Review A · doi:10.1103/physreva.85.042311 · Cited by 464
Self-citationRandomized Benchmarking of Multiqubit Gates
Gaebler, J. P., Meier, A. M., Tan, T. R., Bowler, R., Lin, Y., Hanneke, D., Jost, J. D., Home, J. P., Knill, E., Leibfried, D., et al. (2012) · Physical Review Letters · doi:10.1103/physrevlett.108.260503 · Cited by 127
Cited by
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Kandala, A., Mezzacapo, A., Temme, K., Takita, M., Brink, M., Chow, J. M., & Gambetta, J. M. (2017) · Nature · doi:10.1038/nature23879 · Cited by 2,982
Self-citationSupervised learning with quantum-enhanced feature spaces
Havlíček, V., Córcoles, A. D., Temme, K., Harrow, A. W., Kandala, A., Chow, J. M., & Gambetta, J. M. (2019) · Nature · doi:10.1038/s41586-019-0980-2 · Cited by 2,572
Self-citationSuperconducting Qubits: Current State of Play
Kjaergaard, M., Schwartz, M. E., Braumüller, J., Krantz, P., Wang, J. I.-J., Gustavsson, S., & Oliver, W. D. (2020) · Annual Review of Condensed Matter Physics · doi:10.1146/annurev-conmatphys-031119-050605 · Cited by 1,544
Materials challenges and opportunities for quantum computing hardware
de Leon, N. P., Itoh, K. M., Kim, D., Mehta, K. K., Northup, T. E., Paik, H., Palmer, B. S., Samarth, N., Sangtawesin, S., & Steuerman, D. W. (2021) · Science · doi:10.1126/science.abb2823 · Cited by 710
Tang, H. L., Shkolnikov, V. O., Barron, G. S., Grimsley, H. R., Mayhall, N. J., Barnes, E., & Economou, S. E. (2021) · PRX Quantum · doi:10.1103/prxquantum.2.020310 · Cited by 408
Metadata
- Authors
- Sheldon, S., Magesan, E., Chow, J. M., & Gambetta, J. M.
- Venue
- Physical Review A
- Publisher
- American Physical Society (APS)
- Published
- 2016-06-24
- Volume
- 93
- Issue
- 6
- ISSN
- 0556-2791 (ISSN-L)
- 2469-9926
- 2469-9934
- OpenAlex
- W2298410160
- Cited by
- 477
- References
- 5
- FWCI
- 21.85
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Procedure for systematically tuning up cross-talk in the cross-resonance gate. https://app.cochat.ai/papers/10.1103/physreva.93.060302
- The paper
- Sheldon, S., Magesan, E., Chow, J. M., & Gambetta, J. M. (2016). Procedure for systematically tuning up cross-talk in the cross-resonance gate. Physical Review A. https://doi.org/10.1103/physreva.93.060302
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.
