Fast and accurate flux-crosstalk characterization in superconducting-qubit circuits
Xiao-Yan Yang, Peng Wang, Ran Guo, Hai-Feng Zhang, Tian-Le Wang, Ze-An Zhao, Sheng Zhang, Ren-Ze Zhao, Zhi-Fei Li, Yuan Wu, Zhi-Long Jia, Wei-Cheng Kong, Gang Cao, Peng Duan, Guo-Ping Guo
DOI 10.1103/42lc-rd4t · Physical Review Applied
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Abstract
Tunable coupling architectures consisting of frequency-tunable qubits and couplers are widely employed in superconducting quantum processors. Magnetic flux crosstalk between these components poses a significant challenge to platform scalability, while quantum crosstalk induced by strong qubit-coupler interactions further complicates the compensation of flux crosstalk. To address these issues, we propose and experimentally validate a spin-echo-based method that effectively separates quantum and flux crosstalk, enabling accurate characterization of flux crosstalk. Furthermore, we integrate learning-based algorithm with a high-parallelism measurement scheme to improve efficiency. This approach achieves the stabilization of frequency-shift fluctuations at a noise baseline of approximately 20 kHz, with the accuracy of the crosstalk coefficient reaching an order of 10−5 after compensation. The method provides a robust and efficient framework for mitigating crosstalk, paving the way for high-fidelity control of large-scale quantum processors.
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