Autonomous calibration of superconducting hardware: challenges and opportunities

Robust and reliable software tools for autonomous calibration are essential for advancing quantum computing hardware. Automated cold-start tune-up routines requiring minimal human intervention enable rapid device screening, shortening the verification cycle and accelerating hardware development speed. Simultaneously, maintaining peak device performance requires precise tuning of high-fidelity operations and real-time re-calibration to ensure stability. Achieving all of this relies on a software control suite that is scalable, robust, and fully autonomous.

In this talk, I will present our approach to autonomous tune-up of superconducting qubit hardware, from cold-start bring-up to the system-wide optimization of readout and gate operations. I will share our progress toward a scalable calibration framework, highlight the challenges and opportunities we’ve encountered, and outline our vision for scaling toward the quantum utility regime.