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Li Jing, Ding Hai-Tao, Zhang Dan-Wei
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  • Quantum Fisher information bounds the ultimate precision limit in the parameter estimation and has important applications in quantum metrology. In recent years, the theoretical and experimental studies of non-Hermitian Hamiltonians realized in quantum systems have attracted wide attention. Here, the parameter estimation based on eigenstates of non-Hermitian Hamiltonians is investigated, and the corresponding quantum Fisher information and quantum Cramér-Rao bound for the single-parameter and two-parameter estimations are given. In particular, the quantum Fisher information about estimating intrinsic momentum and external parameters in the non-reciprocal and gain-and-loss Su-Schrieffer-Heeger models, and non-Hermitian versions of the quantum Ising chain, Chern-insulator model and two-level system are calculated and analyzed. For these non-Hermitian models, the results show that in the case of single-parameter estimation in these non-Hermitian models, the quantum Fisher information increases significantly in the gapless regime and near the exceptional points, which can improve the accuracy limit of parameter estimation. For the two-parameter estimation, the determinant of the quantum Fisher information matrix also increases obviously near the gapless and exceptional points. In addition, a higher overall accuracy can be achieved in the topological regime than in the trivial regime, and the topological bound in two-parameter estimation can be determined by the Chern number.
        Corresponding author:Zhang Dan-Wei,danweizhang@m.scnu.edu.cn
      • Funds:Project supported by the National Natural Science Foundation of China (Grant No. 12174126) and the Basic and Applied Basic Research Foundation of Guangdong Province, China (Grant No. 2021A1515010315).
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    • Abstract views:2853
    • PDF Downloads:181
    • Cited By:0
    Publishing process
    • Received Date:26 May 2023
    • Accepted Date:07 July 2023
    • Available Online:18 July 2023
    • Published Online:20 October 2023

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