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    Stable and efficient charging of superconducting capacitively shunted flux quantum batteries

    Li Li1,2,*, Si-Lu Zhao1,2,*, Yun-Hao Shi1, Bing-Jie Chen1,2, Xinhui Ruan1,3, Gui-Han Liang1,2, Wei-Ping Yuan1,2, Jia-Cheng Song1,2, Cheng-Lin Deng1,2 et al.

    Yu Liu1,2, Tian-Ming Li1,2, Zheng-He Liu1,2, Xue-Yi Guo4, Xiaohui Song1,2, Kai Xu1,2,4,5,†, Heng Fan1,2,4,5,‡, Zhongcheng Xiang1,2,5,§, and Dongning Zheng1,2,5,‖

    • *These authors contributed equally to this work.
    • †Contact author: kaixu@iphy.ac.cn
    • ‡Contact author: hfan@iphy.ac.cn
    • §Contact author: zcxiang@iphy.ac.cn
    • ‖Contact author: dzheng@iphy.ac.cn

    Phys. Rev. Applied 24, 054033 – Published 12 November, 2025

    DOI: https://doi.org/10.1103/y3qx-cs3r

    Abstract

    Quantum batteries, as miniature energy storage devices, have sparked significant research interest in recent years. However, achieving rapid and stable energy transfer in quantum batteries while obeying quantum speed limits remains a critical challenge. In this work, we experimentally optimize the charging process by leveraging the unique energy level structure of a superconducting capacitively shunted flux qubit, using counterdiabatic pulses in the stimulated Raman adiabatic passage. Compared to previous studies, we impose two different norm constraints on the driving Hamiltonian, achieving optimal charging without exceeding the overall driving strength. Furthermore, we experimentally demonstrate a charging process that achieves the quantum speed limit. In addition, we introduce a dimensionless parameter S to unify charging speed and stability, offering a universal metric for performance optimization. In contrast to metrics such as charging power and thermodynamic efficiency, the S criterion quantitatively captures the stability of ergotropy while also considering the charging speed. Our results highlight the potential of the capacitively shunted qubit platform as an ideal candidate for realizing three-level quantum batteries and deliver novel strategies for optimizing energy transfer protocols.

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