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arXiv 1705.04516quant-ph
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基于量子费舍尔信息的脉冲驱动量子比特参数估计

Estimation of pulsed driven qubit parameters via quantum Fisher information

N. Metwally, S. S. Hassan

摘要:

我们估计的初始重量和相位参数($θ, ϕ)$的单量子比特系统最初准备在相干态$\ket{θ,ϕ}$和相互作用的三种不同形状的脉冲;矩形,指数,和$sin^2$脉冲。在一般情况下,我们表明,估计程度的权重参数依赖于脉冲形状和初始相位角,$(ϕ)$。对于矩形脉冲的情况,通过Fisher信息函数$(\mathcal{F}_θ)$增加权重参数的估计速率是可能的,其中原子失谐参数的值较小且脉冲强度的值较大。如果初始相位为$ϕ=π/2$,则Fisher信息$(\mathcal{F}_ϕ)$在谐振情况下突然增加以达到其最大值,因此可以以高精度估计相位参数。如果初始系统用经典信息编码,则共振和非共振情况下的Fisher信息的上界要大得多,因此可以以高的估计度估计相位参数。类似地,随着失谐的增加,Fisher信息减少,因此估计相位参数的可能性减少。对于指数脉冲和$sin^2$脉冲,Fisher信息是最大的($\mathcal{F}_{θ,ϕ}=1$),因此总是能够以高精度估计权重和相位参数$(θ,ϕ)$。

英文摘要:

We estimate the initial weight and phase parameters ($θ, ϕ)$ of a single qubit system initially prepared in the coherent state $\ket{θ,ϕ}$ and interacts with three different shape of pulses; rectangular, exponential, and $sin^2$-pulses. In general, we show that the estimation degree of the weight parameter depends on the pulse shape and the initial phase angle, $(ϕ)$. For the rectangular pulse case, increasing the estimating rate of the weight parameter via the Fisher information function $(\mathcal{F}_θ)$ is possible with small values of the atomic detuning parameter and larger values of the pulse strength. Fisher information $(\mathcal{F}_ϕ)$ increases suddenly at resonant case to reach its maximum value if the initial phase $ϕ=π/2$ and consequently one may estimate the phase parameter with high degree of precision. If the initial system is coded with classical information, the upper bounds of Fisher information for resonant and non-resonant cases are much larger and consequently one may estimate the pahse parameter with high degree of estimation. Similarly as the detuning increases the Fisher information decreases and therefore the possibility of estimating the phase parameter decreases. For exponential, and $sin^2$-pulses the Fisher information is maximum ($\mathcal{F}_{θ,ϕ}=1$) and consequently one can always estimate the weight and the phase parameters $(θ,ϕ)$ with high degree of precision.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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