Scaling Alternating-Bias-Assisted Annealing for Precision Transmon Frequency Targeting on Superconducting Quantum Processors
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 σ=0.50±0.05% alongside a component-level yield of ≥ 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∼ 30 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.
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BibTeX
@misc{wang2026scaling,
title = {{Scaling Alternating-Bias-Assisted Annealing for Precision Transmon Frequency Targeting on Superconducting Quantum Processors}},
author = {Xiqiao Wang and Mark Field and Teng Zhang and Xian Wu and Ferhat Aydinoglu and Joel Howard and Angela Q. Chen and Sara Elzeiny and Robert Smith and Timothy McSorley and Nicholas Sharac and Eyob Sete and Alysson Gold and Hilal Cansizoglu and Greg Stiehl and Josh Mutus and Kameshwar Yadavalli and Andrew Bestwick and Stefano Poletto and Raja Katta and David P. Pappas},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2608.27789},
eprint = {2608.27789},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.27789},
}
RIS
TY - UNPB
TI - Scaling Alternating-Bias-Assisted Annealing for Precision Transmon Frequency Targeting on Superconducting Quantum Processors
AU - Xiqiao Wang
AU - Mark Field
AU - Teng Zhang
AU - Xian Wu
AU - Ferhat Aydinoglu
AU - Joel Howard
AU - Angela Q. Chen
AU - Sara Elzeiny
AU - Robert Smith
AU - Timothy McSorley
AU - Nicholas Sharac
AU - Eyob Sete
AU - Alysson Gold
AU - Hilal Cansizoglu
AU - Greg Stiehl
AU - Josh Mutus
AU - Kameshwar Yadavalli
AU - Andrew Bestwick
AU - Stefano Poletto
AU - Raja Katta
AU - David P. Pappas
PY - 2026
DA - 2026/08/27
PB - arXiv
DO - 10.48550/arxiv.2608.27789
UR - https://arxiv.org/abs/2608.27789
AB - 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±0.05% alongside a component-level yield of ≥ 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∼ 30 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.
ER -