Fully autonomous tuning of a spin qubit

Abstract The development of large-scale semiconductor quantum circuits is limited by the difficulties involved in efficiently tuning and operating such circuits. Identifying optimal operating conditions for these qubits is, in particular, complex and involves the exploration of vast parameter spaces. Here we report the autonomous tuning of a semiconductor qubit, from a grounded device to Rabi oscillations. Our approach integrates deep learning, Bayesian optimization and computer vision techniques. We demonstrate this automation in a germanium–silicon core–shell nanowire device. To illustrate the potential of full automation, we characterize how the Rabi frequency and g -factor depend on barrier gate voltages…

• NS
  National Science Foundation
• H2
  Horizon 2020 Framework Programme

  Awards: 951852, 948932, EU H2020, 862046, 824109
• SN
  Swiss Nanoscience Institute
• EA
  Engineering and Physical Sciences Research Council

  Awards: EU H2020, R72976/CN001, H2020