首页|Enhancing quantum metrology for multiple frequencies of oscillating magnetic fields by quantum control

Enhancing quantum metrology for multiple frequencies of oscillating magnetic fields by quantum control

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Quantum multi-parameter estimation has recently attracted increased attention due to its wide applications,with a primary goal of designing high-precision measurement schemes for unknown parameters.While existing research has predominantly concentrated on time-independent Hamiltonians,little has been known about quantum multi-parameter es-timation for time-dependent Hamiltonians due to the complexity of quantum dynamics.This work bridges the gap by investigating the precision limit of multi-parameter quantum estimation for a qubit in an oscillating magnetic field model with multiple unknown frequencies.As the well-known quantum Cramér-Rao bound is generally unattainable due to the potential incompatibility between the optimal measurements for different parameters,we use the most informative bound instead which is always attainable and equivalent to the Holevo bound in the asymptotic limit.Moreover,we apply addi-tional Hamiltonian to the system to engineer the dynamics of the qubit.By utilizing the quasi-Newton method,we explore the optimal schemes to attain the highest precision for the unknown frequencies of the magnetic field,including the simulta-neous optimization of initial state preparation,the control Hamiltonian and the final measurement.The results indicate that the optimization can yield much higher precisions for the field frequencies than those without the optimizations.Finally,we study the robustness of the optimal control scheme with respect to the fluctuation of the interested frequencies,and the optimized scheme exhibits superior robustness to the scenario without any optimization.

quantum metrologymulti-parameter estimationquantum control

雷昕、范静怡、庞盛世

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School of Physics,Sun Yat-sen University,Guangzhou 510275,China

国家自然科学基金

12075323

2024

中国物理B(英文版)
中国物理学会和中国科学院物理研究所

中国物理B(英文版)

CSTPCDEI
影响因子:0.995
ISSN:1674-1056
年,卷(期):2024.33(6)
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