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QuanEstimation: An open-source toolkit for quantum parameter estimation

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arxiv 2205.15588 v3 pith:ZTEFE6QD submitted 2022-05-31 quant-ph hep-thphysics.comp-ph

QuanEstimation: An open-source toolkit for quantum parameter estimation

classification quant-ph hep-thphysics.comp-ph
keywords boundsmethodsoptimizationquantumtoolkitdesignestimationparameter
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Quantum parameter estimation promises a high-precision measurement in theory, however, how to design the optimal scheme in a specific scenario, especially under a practical condition, is still a serious problem that needs to be solved case by case due to the existence of multiple mathematical bounds and optimization methods. Depending on the scenario considered, different bounds may be more or less suitable, both in terms of computational complexity and the tightness of the bound itself. At the same time, the metrological schemes provided by different optimization methods need to be tested against realization complexity, robustness, etc. Hence, a comprehensive toolkit containing various bounds and optimization methods is essential for the scheme design in quantum metrology. To fill this vacancy, here we present a Python-Julia-based open-source toolkit for quantum parameter estimation, which includes many well-used mathematical bounds and optimization methods. Utilizing this toolkit, all procedures in the scheme design, such as the optimizations of the probe state, control and measurement, can be readily and efficiently performed.

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  1. Iterative optimization in quantum metrology and entanglement theory using semidefinite programming

    quant-ph 2022-06 unverdicted novelty 5.0

    An iterative semidefinite programming method maximizes quantum Fisher information over local Hamiltonians to optimize metrological performance of quantum states and solves related entanglement problems.