Regensburg 2022 – scientific programme

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QI: Fachverband Quanteninformation

QI 13: Implementations: Superconducting Qubits

QI 13.2: Talk

Friday, September 9, 2022, 10:00–10:15, H8

Test and diagnostics speed up for characterizing few-qubit superconducting quantum processors — •Thorsten Last, Garrelt Alberts, Adam Lawrence, Kelvin Loh, Viacheslav Ostroukh, and Adriaan Rol — Orange Quantum Systems B.V., Lorentzweg 1, 2628 CJ Delft, NL

The combined challenge of increasing the qubit count on a quantum processor and a requirement to further reduce the qubit's error rates require novel approaches in test and qubit diagnostics. An important aspect to improve the situation is an acceleration of the development cycle for quantum processors [1]. Here we present benchmarking and diagnostic tools based on the recently established open-source platform Quantify [2] to perform end-to-end data analytics. Structured (human-assisted) characterization and a gradual enhancement of automation already led to a reduction of time for basic qubit diagnostics from months to days. The diagnostic tools for characterizing small scale superconducting quantum processors are available as software packages or fully integrated into room temperature electronic control racks. They are organized in complexity classes ranging from hardware verification, and basic single-qubit analytics up to the level of algorithmic benchmarking. Besides quantum processor diagnostics these tools are also used for full-stack system verification through experiment. [1] G.J.N. Alberts, et al., EPJ Quantum Technol. 8: 18 (2021). [2] https://quantify-quantify-core.readthedocs-hosted.com/en/0.5.3_a/