Estimating phase with a random generator: Strategies and resources in multiparameter quantum metrology

Yousefjani, Rozhin; Nichols, Ralph C.; Salimi, S.; Adesso, Gerardo

doi:10.1103/physreva.95.062307

Cited by 20 publications

(22 citation statements)

References 70 publications

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“…estimation strategies. These two strategies generate different precision scalings in the count resource [276][277][278] and the time resource 204,208,218 . However, no clear results have been found that determine when either strategy should be preferred.…”

Section: Distributed Quantum Sensingmentioning

confidence: 99%

Geometric perspective on quantum parameter estimation

Sidhu

Kok

2020

AVS Quantum Science

176

132

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Quantum metrology holds the promise of an early practical application of quantum technologies, in which measurements of physical quantities can be made with much greater precision than what is achievable with classical technologies. In this review, we collect some of the key theoretical results in quantum parameter estimation by presenting the theory for the quantum estimation of a single parameter, multiple parameters, and optical estimation using Gaussian states. We give an overview of results in areas of current research interest, such as Bayesian quantum estimation, noisy quantum metrology, and distributed quantum sensing. We address the question how minimum measurement errors can be achieved using entanglement as well as more general quantum states. This review is presented from a geometric perspective. This has the advantage that it unifies a wide variety of estimation procedures and strategies, thus providing a more intuitive big picture of quantum parameter estimation. CONTENTS

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Section: Distributed Quantum Sensingmentioning

confidence: 99%

Geometric perspective on quantum parameter estimation

Sidhu

Kok

2020

AVS Quantum Science

176

132

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“…Indeed, the capability of obtaining quantum-enhanced performances in the multiparameter case is particularly relevant [9], since a large variety of estimation problems involve more than a single physical quantity. Notable examples are phase imaging [10][11][12], measurements on biological systems [13,14], magnetic field imaging [15], gravitational waves parameters estimation [16,17], sensing technologies [18,19], quantum sensing networks [20], quantum process tomography [21][22][23][24] and state estimation [25].…”

Section: Introductionmentioning

confidence: 99%

Experimental multiphase estimation on a chip

Polino¹,

Riva²,

Valeri³

et al. 2019

Optica

116

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Multiparameter estimation is a general problem that aims at measuring unknown physical quantities, obtaining high precision in the process. In this context, the adoption of quantum resources promises a substantial boost in the achievable performances with respect to the classical case. However, several open problems remain to be addressed in the multiparameter scenario. A crucial requirement is the identification of suitable platforms to develop and experimentally test novel efficient methodologies that can be employed in this general framework. We report the experimental implementation of a reconfigurable integrated multimode interferometer designed for the simultaneous estimation of two optical phases. We verify the high-fidelity operation of the implemented device, and demonstrate quantum-enhanced performances in two-phase estimation with respect to the best classical case, post-selected to the number of detected coincidences. This device can be employed to test general adaptive multiphase protocols due to its high reconfigurability level, and represents a powerful platform to investigate the multiparameter estimation scenario.

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“…These studies have shown that a super-extensive growth of the frequency sensitivity may still be attained under time-inhomogeneous, phase-covariant noise [26][27][28][29][30], and even more generic Ohmic dissipation [31], noise with a particular geometry [32,33], or setups related to quantum error correction [34][35][36]. See also [37,38] which question the role of entanglement in such schemes and give advice on practical implementations. In general, these studies have shown that, while the 1/n precision scaling in frequency estimation may not be available in the presence of noise, it is possible to achieve a scaling that goes as n 1 3 4 , n 1 5 6 , or n 1 7 8 depending on the details of the problem.…”

Section: Introductionmentioning

confidence: 99%

Noisy frequency estimation with noisy probes

et al. 2018

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We consider frequency estimation in a noisy environment with noisy probes. This builds on previous studies, most of which assume that the initial probe state is pure, while the encoding process is noisy, or that the initial probe state is mixed, while the encoding process is noiseless. Our work is more representative of reality, where noise is unavoidable in both the initial state of the probe and the estimation process itself. We prepare the probe in a GHZ diagonal state, starting from n+1 qubits in an arbitrary uncorrelated mixed state, and subject it to parameter encoding under dephasing noise. For this scheme, we derive a simple formula for the (quantum and classical) Fisher information, and show that quantum enhancements do not depend on the initial mixedness of the qubits. That is, we show that the so-called 'Zeno' scaling is attainable when the noise present in the encoding process is time inhomogeneous. This scaling does not depend on the mixedness of the initial probe state, and it is retained even for highly mixed states that can never be entangled. We then show that the sensitivity of the probe in our protocol is invariant under permutations of qubits, and monotonic in purity of the initial state of the probe. Finally, we discuss two limiting cases, where purity is either distributed evenly among the probes or concentrated in a single probe.

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Estimating phase with a random generator: Strategies and resources in multiparameter quantum metrology

Cited by 20 publications

References 70 publications

Geometric perspective on quantum parameter estimation

Geometric perspective on quantum parameter estimation

Experimental multiphase estimation on a chip

Noisy frequency estimation with noisy probes

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