Experimental multiphase estimation on a chip

Polino, Emanuele; Riva, Martina; Valeri, Mauro; Silvestri, Raffaele; Corrielli, Giacomo; Crespi, Andrea; Spagnolo, Nicolò; Osellame, Roberto; Sciarrino, Fabio

doi:10.1364/optica.6.000288

Cited by 93 publications

(121 citation statements)

References 69 publications

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“…Multiparameter estimation has general scope beyond this application, and many instances have shown a tradeoff in the achievable precision on the parameters to be estimated ,including multiple phases, phase and phase diffusion, etc. [15][16][17]. Such trade-offs do not impact on the capabilities of the Bayesian technique to provide a reliable estimator for many parameters at once.…”

Section: Bayesian Estimation In the Presence Of Noisementioning

confidence: 99%

Assessing Data Postprocessing for Quantum Estimation

Gianani

Genoni

Barbieri

2020

IEEE J. Select. Topics Quantum Electron.

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Quantum sensors are among the most promising quantum technologies, allowing to attain the ultimate precision limit for parameter estimation. In order to achieve this, it is required to fully control and optimize what constitutes the hardware part of the sensors, i.e. the preparation of the probe states and the correct choice of the measurements to be performed. However careful considerations must be drawn also for the software components: a strategy must be employed to find a so-called optimal estimator. Here we review the most common approaches used to find the optimal estimator both with unlimited and limited resources. Furthermore, we present an attempt at a more complete characterization of the estimator by means of higher-order moments of the probability distribution, showing that most information is already conveyed by the standard bounds.

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Section: Bayesian Estimation In the Presence Of Noisementioning

confidence: 99%

Assessing Data Postprocessing for Quantum Estimation

Gianani

Genoni

Barbieri

2020

IEEE J. Select. Topics Quantum Electron.

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“…It is an integral part of quantum communication and has significant potential for upscaling quantum computer technologies that are otherwise not scalable [3]. Recently, it was realized that sensing of multiple spatially distributed parameters may also benefit from an entangled quantum network [4][5][6][7][8][9]. Here we experimentally demonstrate how sensing of an averaged phase shift among four distributed nodes benefits from an entangled quantum network.…”

mentioning

confidence: 91%

Distributed quantum sensing in a continuous-variable entangled network

et al. 2019

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Networking plays a ubiquitous role in quantum technology [1, 2]. It is an integral part of quantum communication and has significant potential for upscaling quantum computer technologies that are otherwise not scalable [3]. Recently, it was realized that sensing of multiple spatially distributed parameters may also benefit from an entangled quantum network [4][5][6][7][8][9]. Here we experimentally demonstrate how sensing of an averaged phase shift among four distributed nodes benefits from an entangled quantum network. Using a four-mode entangled continuous variable (CV) state, we demonstrate deterministic quantum phase sensing with a precision beyond what is attainable with separable probes. The techniques behind this result can have direct applications in a number of primitives ranging from biological imaging to quantum networks of atomic clocks.Quantum noise associated with quantum states of light and matter ultimately limits the precision by which measurements can be carried out [10][11][12]. However, by carefully designing the coherence of this quantum noise to exhibit properties such as entanglement and squeezing, it is possible to measure various physical parameters with significantly improved sensitivity compared to classical sensing schemes. Numerous realizations of quantum sensing utilizing non-classical states of light [2,13,15] and matter [16] have been reported, while only a few applications have been explored. Examples are quantum-enhanced gravitational waves interferometry [17], detection of magnetic fields [18][19][20] and sensing of the viscous-elasticity parameter of yeast cells [21]. All these implementations are, however, restricted to the sensing of a single parameter at a single location.Spatially distributed sensing of parameters at multiple locations in a network is relevant for applications from local beam tracking [22] to global scale clock synchronization [4]. The development of quantum networks [1, 2,23,24] enables new strategies for enhanced performance in such scenarios. Theoretical works [5][6][7][8][25][26][27][28] have shown that entanglement can improve sensing capabilities in a network using either twin-photons * or Greenberger-Horne-Zeilinger (GHZ) states combined with photon number resolving detectors [6,7] or using CV entanglement for the detection of distributed phase space displacements [8]. In this Letter, we experimentally demonstrate an entangled CV network for sensing of multiple phase shifts inspired by the theoretical proposal of Ref. [8]. Moreover, for the first time in any system, we demonstrate deterministic distributed sensing in a network of four nodes with a sensitivity beyond that achievable with a separable approach using similar quantum states. BSN … vaccum vaccum S a b c d FIG. 1.Distributed phase sensing scheme. The task is to estimate the average value of M spatially distributed phase shifts φ1, . . . , φM . (a) Without a network, the average phase shift must be estimated by probing each sample individually. This can be done with homodyne detection of the...

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“…Discussion and conclusions.-Our method provides a powerful and novel framework to study schemes with limited data and moderate prior knowledge, a regime of practical interest and normally out of the scope of other techniques in the literature. Taking into account that we are starting to witness the experimental implementation of multi-parameter protocols [59,60], our proposal could play a crucial role in the design of future experiments.…”

mentioning

confidence: 99%

Bayesian multiparameter quantum metrology with limited data

Rubio

Dunningham

2020

Phys. Rev. A

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A longstanding problem in quantum metrology is how to extract as much information as possible in realistic scenarios, which typically involve multiple parameters, limited measurement data and some degree of prior information. Here we present a practical strategy for achieving just this. First we derive a new Bayesian multi-parameter quantum bound. We then show how to construct the optimal measurement when our bound can be saturated for a single shot and consider experiments involving a repeated sequence of these measurements. Our method properly accounts for the number of measurements and the degree of prior information, and we illustrate our ideas with a qubit sensing network and a model for phase imaging. This approach provides a powerful and useful technique for implementing quantum metrology in a wide-range of practical scenarios as well as gaining new insights about the role of local and global strategies.

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Experimental multiphase estimation on a chip

Cited by 93 publications

References 69 publications

Assessing Data Postprocessing for Quantum Estimation

Assessing Data Postprocessing for Quantum Estimation

Distributed quantum sensing in a continuous-variable entangled network

Bayesian multiparameter quantum metrology with limited data

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