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QuanEstimation.jl

GitHub release (latest by date) License: BSD-3-Clause Downloads DOI

QuanEstimation.jl is an open-source toolkit for quantum parameter estimation, which can be used to perform general evaluations of many metrological tools and scheme designs in quantum parameter estimation. This package is is also the computional core of QuanEstimation.

Installation

Run the command in the julia REPL to install QuanEstimation:

julia > using Pkg 

julia > Pkg.add("QuanEstimation")

Documentation

The documentation for QuanEstimation.jl is here, and the documentation for both QuanEstimation and QuanEstimation.jl is here.

Citation

If you use QuanEstimation in your research, please cite the following papers:

[1] M. Zhang, H.-M. Yu, H. Yuan, X. Wang, R. Demkowicz-Dobrzański, and J. Liu, QuanEstimation: An open-source toolkit for quantum parameter estimation, Phys. Rev. Res. 4, 043057 (2022).

[2] H.-M. Yu and J. Liu, QuanEstimation.jl: An open-source Julia framework for quantum parameter estimation, Fundam. Res. (2025).

  • Development of the GRAPE algorithm:

    • auto-GRAPE:

      M. Zhang, H.-M. Yu, H. Yuan, X. Wang, R. Demkowicz-Dobrzański, and J. Liu,
      QuanEstimation: An open-source toolkit for quantum parameter estimation,
      Phys. Rev. Res. 4, 043057 (2022).

    • GRAPE for single-parameter estimation:

      J. Liu and H. Yuan, Quantum parameter estimation with optimal control,
      Phys. Rev. A 96, 012117 (2017).

    • GRAPE for multiparameter estimation:

      J. Liu and H. Yuan, Control-enhanced multiparameter quantum estimation,
      Phys. Rev. A 96, 042114 (2017).

About

QuanEstimation.jl is an open-source toolkit for quantum parameter estimation and also the computational core of the Python-Julia package QuanEstimation

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