We investigate a scheme to improve the precision of parameter estimation using no-knowledge measurement-based feedback control. The scheme shows that combination of no-knowledge measurement-based feedback control and quantum weak measurement is the optimal way to suppress decoherence. Our results indicate that compared with knowledge quantum feedback control, under the same weak measurement condition, the precision of parameter estimation can be improved more effectively with no knowledge quantum feedback control. Further, based on numerical simulation, we find that the feedback operator is chosen as [Formula: see text] (or both [Formula: see text] and [Formula: see text], which can protect quantum Fisher information (QFI) for a long time.
In quantum information technologies, quantum weak measurement is beneficial for protecting coherence of systems. In order to further improve the protection effect of quantum weak measurement on coherence, we propose an optimization scheme of quantum Fisher information (QFI) protection in an open quantum system by combing no-knowledge quantum feedback control with quantum weak measurement. On the basis of solving the dynamic equations of a stochastic two-level quantum system under feedback control, we compare the effects of different feedback Hamiltonians on QFI and find that via no-knowledge quantum feedback, the observation operator σx (or σx and σz ) can protect QFI for a long time. Namely, no-knowledge quantum feedback can improve the estimation precision of feedback coefficient as well as that of detection coefficient.
We investigate that no-knowledge measurement-based feedback control is utilized to obtain the estimation precision of the detection efficiency. For the feedback operators that concern us, no-knowledge measurement is the optimal way to estimate the detection efficiency. We show that the higher precision can be achieved for the lower or larger detection efficiency. It is found that no-knowledge feedback can be used to cancel decoherence. No-knowledge feedback with a high detection efficiency can perform well in estimating frequency and detection efficiency parameters simultaneously. And simultaneous estimation is better than independent estimation given by the same probes.
Various schemes have been proposed to overcome the drawback of the decoherence on quantum-enhanced parameter estimation. Here we suggest an alternative method, quantum feedback, to enhance the parameter precision of optimal quantum estimation of a dissipative qubit by investigating its dynamics of quantum Fisher information. We find that compared with the case without feedback, the quantum Fisher information of the dissipative qubit in the case of feedback has a large maximum value in time evolution and a smaller decay rate in the long time.
Abstract We investigate the effect of the weak measurement (WM) and quantum measurement reversal (QMR) on the improvement of the precision of parameter estimation for a qubit interacting with various non-Markovian decoherence sources: amplitude damping, dephasing damping and random unitary damping, respectively. We derive the exact expressions of the optimal quantum Fisher information, show explicitly that the WM and QMR operation indeed helps for enhancing the precision of parameter estimation from amplitude damping and phase damping, but not for random unitary damping. In particular, we found that the enhancement effect is independent of the specific form of the spectral density of the reservoir, which extends the applicable scope of the WM and QMR approach.
The weak-value amplification is extensively considered in precision metrology in order to achieve a higher sensitivity. Despite the practical benefits in amplifying small physical quantities, its metrological advantage still arouses a broad debate due to the low postselection probability of success. In this paper, by employing the quantum Fisher information metric, we show that the precision of estimating an unknown parameter can be improved by introducing a precoupling process with properly chosen interaction operators. We point out this result is credible for both real and imaginary weak values. By tracking the meter wave functions, we find this enhancement of estimation precision comes from a precoupling induced modulation of the meter wave function, thus the most sensitive regime with respect to the parameter is reached. In addition, the estimation error is investigated by considering the difference between the theoretical and estimated value. The analysis suggests that this kind of error can be effectively suppressed by averaging the estimations resulted from different initial meter states. These results are finally illustrated by an exact numerical simulation where the advantages of our proposal are displayed by the comparison to the standard weak-value amplification scheme.
Recently, Zhong et al. [Phys. Rev. A 87, 022337(2013)] investigated the dynamics of quantum Fisher information (QFI) in the presence of decoherence. We here reform their results and propose two schemes to enhance and preserve the QFIs for a qubit system subjected to a decoherence noisy environment by applying
non-Hermitian operators process. The proposed schemes are related to the
prior (or the
post ) non-Hermitian operator process corresponding to before (or after) the interest system suffers from decoherence, respectively. Resorting to the Bloch sphere representation, we derive the exact analytical expressions of the QFIs with respect to the amplitude parameter
θ and the phase parameter
ϕ, and in detail investigate the influence of
non-Hermitian operator parameters on the QFIs. Compared with purity decoherence process (without non-Hermitian operator process), we find that the
post non-Hermitian operator process can potentially enhance and preserve the QFIs by choosing appropriate
non-Hermitian operator parameters, while with the help of the
prior non-Hermitian operator process one could completely eliminate the effect of decoherence to improve the parameters estimation. Finally, a generalized non-Hermitian operator parameters effect on the parameters estimation is also considered.