Demonstrated gate-tunable supercurrents in Josephson junctions on Ge quantum wells with Ic >100 nA and IcRn=8.63 μV using in-situ Al contacts and deep mesa etch for low-loss integration.
Paladino , author Y
2 Pith papers cite this work. Polarity classification is still indexing.
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Machine learning classifies six Markovian and non-Markovian noise classes in two-qubit systems with over 94% accuracy using only final transfer efficiencies from a coherent population transfer protocol under three driving conditions.
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Voltage-tunable Josephson Junctions on Germanium Quantum Wells with in-situ Aluminum Contacts
Demonstrated gate-tunable supercurrents in Josephson junctions on Ge quantum wells with Ic >100 nA and IcRn=8.63 μV using in-situ Al contacts and deep mesa etch for low-loss integration.
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Detection of noise correlations in two qubit systems by Machine Learning
Machine learning classifies six Markovian and non-Markovian noise classes in two-qubit systems with over 94% accuracy using only final transfer efficiencies from a coherent population transfer protocol under three driving conditions.