2014
DOI: 10.1103/physreva.90.063619
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Parameter estimation in memory-assisted noisy quantum interferometry

Abstract: We demonstrate that memory in an N -qubit system subjected to decoherence, is a potential resource for the slow-down of the entanglement decay. We show that this effect can be used to retain the sub shot-noise sensitivity of the parameter estimation in quantum interferometry. We calculate quantum Fisher information, which sets the ultimate bound for the precision of the estimation. We also derive the sensitivity of such a noisy interferometer, when the phase is either estimated from the measurements of the pop… Show more

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Cited by 19 publications
(43 citation statements)
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“…We stress thatF Q is actually the object utilized in more phenomenological approaches to quantum metrology, where the master equation is postulated to describe some specific kinds of noise, rather than microscopically derived so that the contributions due to the dependence of the rates on ω 0 are not accounted for. On the other hand, let us mention that in [35] the role of the dependence of the emission and absorption rates on the free system frequency for a qubit system coupled to a Gaussian classical noise has been investigated. Figure 5(c) summarizes the effects of the two contributions described above.…”
Section: Different Contributions To the Qfimentioning
confidence: 99%
“…We stress thatF Q is actually the object utilized in more phenomenological approaches to quantum metrology, where the master equation is postulated to describe some specific kinds of noise, rather than microscopically derived so that the contributions due to the dependence of the rates on ω 0 are not accounted for. On the other hand, let us mention that in [35] the role of the dependence of the emission and absorption rates on the free system frequency for a qubit system coupled to a Gaussian classical noise has been investigated. Figure 5(c) summarizes the effects of the two contributions described above.…”
Section: Different Contributions To the Qfimentioning
confidence: 99%
“…When n is large enough, e.g.,n=20 (see the figure), there is a sharp improvement in precision as the success probability approaches the critical value. In the asymptotic limit,  ¥ n , it gives rise to a critical behavior that interpolates between the ultimate precision limit, equation (25), and the precision for finite values ofS, equation (26). Figure 4 shows the scaling of the uncertainty with the amount of resources, n, for low levels of noise = r 95% and for different values of the abstention probabilityS.…”
Section: Finite Nmentioning
confidence: 99%
“…The pre-factorr takes into account the scaling of the variance of the state equation (24) as compared to the pure-state case. The first equality of equation (26) uses the fact that only abstention on blocks about the typical spinj 0 is affordable for finite S. This also fixes the value ofS to be approximately s j 0 . The simple expression on the right of equation (26) is not an exact bound, but does provide a good approximation for moderate values ofS (see figure 3).…”
Section: Multiple-copiesmentioning
confidence: 99%
“…We restricted our calculations only to pure states and assumed that the interactions are fully suppressed during the interferometric sequence. We did not take into account the impact of decoherence [36][37][38]. In any realistic application, the above theory should be extended to include those effects.…”
Section: Discussionmentioning
confidence: 99%
“…On the other hand, such a state is Gaussian, meaning that it is characterized by the two lowest correlation functions. Not surprisingly, in such a case the sensitivity, which depends on these two moments (38), is as powerful as the estimation from the full probability (31). To summarize, at ϕ = π the simple estimation protocol from the average population imbalance is optimal, i.e., it saturates the ultimate bound of the QFI.…”
Section: Estimation From the Population Imbalancementioning
confidence: 99%