Tuning Arrays with Rays: Physics-Informed Tuning of Quantum Dot Charge States
Joshua Ziegler, Florian Luthi, Mick Ramsey, Felix Borjans, Guoji Zheng, Justyna P. Zwolak · Physical Review Applied · 2023
Many methods to automatically tune silicon spin qubits are limited by reliability and data efficiency, which makes them less likely to be scalable. The authors demonstrate a reliable, efficient, physics-informed tuning algorithm (PIT) for navigating to a target charge configuration⏤a prerequisite to forming qubits. This tuning method combines machine learning and physical intuition with an algorithm that leverages one-dimensional scans (rays) and conventional peak-finding to navigate from a coarse, unknown device state to a desired charge occupation efficiently and effectively. PIT enables the transformation of an uncalibrated circuit to a functioning quantum processor.