Cloud-tested quantum noise model predicts superconducting qubit errors with sevenfold better accuracy
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.Quantum Physics NewsRead More
New cryogenic silicon carbide hardware addresses quantum computing bottleneck
Researchers from the Department of Electrical and Computer Engineering in the Faculty of Engineering at the University of Hong Kong (HKU) and the Centre for Advanced Semiconductors and Integrated Circuits (CASIC) have achieved a major breakthrough in cryogenic electronics. The team has developed a programmable neuromorphic hardware platform that operates near absolute zero, providing a
