Scaling Alternating-Bias-Assisted Annealing for Precision Transmon Frequency Targeting on Superconducting Quantum Processors

Authors:Xiqiao Wang, Mark Field, Teng Zhang, Xian Wu, Ferhat Aydinoglu, Joel Howard, Angela Q. Chen, Sara Elzeiny, Robert Smith, Timothy McSorley, Nicholas Sharac, Eyob Sete, Alysson Gold, Hilal Cansizoglu, Greg Stiehl, Josh Mutus, Kameshwar Yadavalli, Andrew Bestwick, Stefano Poletto, Raja Katta, David P. Pappas

Abstract:Recent advances in the alternating-bias-assisted annealing (ABAA) technique have successfully mitigated intrinsic Josephson-junction (JJ) fabrication variations. This new technique enables precision qubit frequency tuning alongside simplicity. However, it is critical to enhance tuning throughput and yield while investigating the factors that drive targeting performance as the technology scales. Here, we characterize ABAA tuning performance within a 150-mm wafer process flow and extend this technique to simultaneous, multi-channel tuning, demonstrating that a wafer-scale JJ resistance tuning precision of $\sigma=0.50\pm0.05\%$ alongside a component-level yield of $\ge 98.8\%$ can be achieved. Furthermore, we demonstrate a strong correlation between yield, tuning speed, and junction breakdown voltage, establishing the latter as a vital process control parameter for meeting production goals. Finally, we demonstrate a successful implementation of ABAA tuning on a quad-module quantum processor (Rigetti Cepheus-1-36Q), where we achieve an empirical frequency targeting precision of $\sigma \sim 30\text{ MHz}$ in both qubit and qubit-qubit detuning frequencies, contributing to high median two-qubit gate fidelities. These results confirm the efficacy and scalability of ABAA for high-precision Hamiltonian targeting, a critical enabler for modular superconducting quantum processor technology.

arXiv:2608.27789 [quant-ph]

(or arXiv:2608.27789v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2608.27789 arXiv-issued DOI via DataCite (pending registration)