Toward Automated Tuning and Charge-State Characterization of Accumulation-Mode Silicon Quantum-Dot Devices

Abstract

Silicon quantum dots are an exceedingly promising platform for scalable quantum processors, backed by a well-established industry of semiconductor fabrication. Gate-defined processors are limited by the time required to tune, as well as the increasing complexity, scaled by the number of gates in the system. This thesis presents an algorithmic approach for automated tuning as a means of tackling these challenges.

Each gate in the dot system represents one additional dimension of the voltage space one must explore to find an optimal operating regime. Including fabrication imperfections and variability, the desirable operating points of the parameter space for a given device are unique and require some time to determine, through multiple avenues of measurement and analysis. The work presented in this thesis advances the group’s current autotuning capabilities, with the partial automatic tuning of a triple quantum dot, accompanied by a charge sensor. This advancement proposes an extension of the previous protocol for use on quantum dots as qubits, as well as an algorithm for automatic calibration and detection of single electron tunneling events by the charge sensor. This algorithm culminates in the automatic measurement of a charge stability diagram. The charge-sensor calibration and initialization of the triple dot system completed successfully in 20 of 20 runs, with a typical runtime of approximately 8.5 hours. The automatic charge stability diagram measurement was successful for one of the two pairs of double dots, with a typical runtime of 7 hours in total. Additionally, this work proposes algorithmic approaches for gate virtualization and identification of specific charge states for the triple dot and charge sensor system. This approach was applied and demonstrated on non-virtualized charge stability diagram data, and successfully detected all visible charge transitions from the measured data. Finally, this thesis demonstrates the manual measurement of bias triangles, as well as proposes a method for automatic detection of Pauli spin blockade, using bias triangles, though the results were inconclusive. These algorithms would allow for focus on the development of readout methods, qubit characterization, and quantum gate and circuit implementations.

The algorithms require a priori knowledge of the device and thus are limited in their immediate application to quantum dot devices as a whole. However, these advancements serve as a strong stepping stone towards a more general autotuning protocol. The work in this thesis is therefore applicable to many subsequent quantum dot experiments the group will undertake.