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Cloud-tested quantum noise model predicts superconducting qubit errors with sevenfold better accuracy
- June 8, 2026 at 11:00 PM
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Researchers from the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, and Johns Hopkins University in Baltimore have developed a practical, comprehensive noise-modeling framework for a popular class of superconducting quantum processors. Their work, published in the journal PRX Quantum, offers a sevenfold improvement in predictive accuracy over existing approaches.
Originally published at Phys.org