Master's Defense: Lara Lausen

Automation of tuning strategies for spin qubits - from 2DEG to quantum dot

Spin qubits are a promising candidate for quantum information processing. They are implemented using semiconductor-based quantum dots and hence successful implementation requires the fine-tuning of voltages to the quantum dot regime to ensure an optimal performance. Adjusting and finding the optimal voltage configuration for a quantum device is a challenging task that requires skilled specialists and can consume a considerable amount of time. With the need for scalable quantum technologies it is not efficient to rely solely on human experts, and automation techniques are vital for the further development. This work investigates tuning strategies for spin qubits to operate in the quantum dot regime and how to automate these. The work is divided into four main parts. It starts with providing a comprehensive theoretical background, including the principles of quantum computing and the use of spin qubits as a platform for quantum information processing. Secondly, manual tuning strategies for a specific device are developed and optimized to achieve efficient and reliable operation of the specific spin qubit. Thirdly, an automated tuning algorithm based on the manual tuning strategy is developed and implemented, enabling fast and accurate tuning of the spin qubits, using analysis and fitting techniques. Finally, the thesis concludes with an outlook on future developments in the field.