用于超导量子处理器上Transmon量子比特频率精准定位的交替偏置辅助退火（ABAA）技术的规模化
Scaling Alternating-Bias-Assisted Annealing for Precision Transmon Frequency Targeting on Superconducting Quantum Processors
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中文总结 AI 辅助
本文将交替偏置辅助退火（ABAA）技术规模化，实现晶圆级约瑟夫森结电阻调谐精度σ=0.50±0.05%、器件良率≥98.8%，在Rigetti Cepheus-1-36Q量子处理器上达到频率定位精度σ≈30 MHz，为模块化超导量子处理器提供关键支持。
中文摘要 AI 辅助
交替偏置辅助退火（ABAA）技术的最新进展已成功缓解了约瑟夫森结（JJ）制造的固有偏差，该新技术在实现量子比特频率精准调谐的同时具备操作简便的优势。然而，随着技术规模化，提升调谐吞吐量与良率、研究影响定位性能的关键因素至关重要。本文在150毫米晶圆工艺流程中表征了ABAA调谐性能，并将该技术扩展至多通道同步调谐，实现了晶圆级JJ电阻调谐精度σ=0.50±0.05%，同时器件级良率≥98.8%。此外，本文证实了良率、调谐速度与结击穿电压之间存在强相关性，确立了结击穿电压作为满足生产目标的关键工艺控制参数。最后，本文在四模块量子处理器（Rigetti Cepheus-1-36Q）上成功实现了ABAA调谐，在量子比特频率及量子比特间失谐频率上均达到了σ≈30 MHz的经验定位精度，助力实现较高的中位两量子比特门保真度。这些结果证实了ABAA在高精度哈密顿量定位方面的有效性与可扩展性，而这正是模块化超导量子处理器技术的关键推动因素。
英文摘要
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 $σ=0.50\pm0.05\%$ 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 $σ\sim 30\text{ MHz}$ 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.
