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Gregory Quiroz

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Cloud-tested quantum noise model predicts superconducting qubit errors with sevenfold better accuracy

Cloud-tested quantum noise model predicts superconducting qubit errors with sevenfold better accuracy Gaby Clark Scientific Editor Robert Egan Associate Editor 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...

Phys.org 1d ago