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Radio-frequency measurements could satisfy DiVincenzo's readout criterion infuture large-scale solid-state quantum processors, as they allow for highbandwidths and frequency multiplexing. However, the scalability potential ofthis readout technique can only be leveraged if quantum device tuning isperformed using exclusively radio-frequency measurements i.e. without resortingto current measurements. We demonstrate an algorithm that automatically tunesdouble quantum dots using only radio-frequency reflectometry. Exploiting thehigh bandwidth of radio-frequency measurements, the tuning was completed withina few minutes without prior knowledge about the device architecture. Ourresults show that it is possible to eliminate the need for transportmeasurements for quantum dot tuning, paving the way for more scalable devicearchitectures.

All rf-based tuning algorithm for quantum devices using machine learning