Quantum enhanced phase retrieval

Liberman, Liat; Israel, Yonatan; Poem, Eilon; Silberberg, Yaron

doi:10.1364/optica.3.000193

Cited by 14 publications

(13 citation statements)

References 31 publications

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“…As in other memory-effect based modalities, our new protocol is restricted in terms of scattering layers to go through by the angular memory effect range which is very limited in biological tissues 6 7 36 , however, those modalities have an infinite DOF and thus lack the ability to distinguish depth within a scene or an object 7 . Moreover, phase retrieval algorithms which are used in these studies impose strict limitations on the complexity of the objects that can be imaged and do not guarantee convergence to an unambiguous correct solution 37 38 ; this is not a concern in our imaging protocol. However, it is important to note that in order to achieve these features, our protocol requires to have information about the PSF of the scattering medium.…”

Section: Resultsmentioning

confidence: 99%

Memory-effect based deconvolution microscopy for super-resolution imaging through scattering media

Edrei

Scarcelli

2016

Sci Rep

142

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High-resolution imaging through turbid media is a fundamental challenge of optical sciences that has attracted a lot of attention in recent years for its wide range of potential applications. Here, we demonstrate that the resolution of imaging systems looking behind a highly scattering medium can be improved below the diffraction-limit. To achieve this, we demonstrate a novel microscopy technique enabled by the optical memory effect that uses a deconvolution image processing and thus it does not require iterative focusing, scanning or phase retrieval procedures. We show that this newly established ability of direct imaging through turbid media provides fundamental and practical advantages such as three-dimensional refocusing and unambiguous object reconstruction.Imaging performances of traditional optical systems quickly degrade with increasing scattering 1,2 , so that in the diffusive regime only low resolution optical images can be obtained 3,4 . However, recently, novel strategies such as phase conjugation, scattering-matrix inversion, ultrasonic encoding or the so-called "memory effect" have revolutionized this field showing high resolution imaging and focusing behind turbid tissue up to several scattering lengths [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] . In many of these studies, the ability to image through turbid media is facilitated by additional information gathered on the scattering medium. For example, placing a "guide-star" in the object plane, iterative algorithms have been used to correct for the aberrations induced by the medium 10 ; or the scattered field has been recorded and reversed to focus or scan the light back onto the object plane 20,21 . Here, we use the fundamental principles of the memory effect to enable direct wide-field imaging through turbid media using deconvolution image processing and a single-shot of the scattered intensity pattern. This enabled us to achieve, through turbid media, many of the same powerful features of standard deconvolution microscopy such as improved resolution as well as three-dimensional refocusing.The memory-effect, first described in the 1980's, is a peculiar phenomenon observed when light propagates through a scattering medium 22,23 . Within a certain range of impinging angles, known as the memory-effect angular range, the seemingly-random speckle patterns observed after the scattering medium are highly correlated. Deconvolution processing is a well-established and widely used technique in astronomy 24 , microscopy 25 as well as non-optical imaging 26 . It relies on the linear properties of imaging systems for which the imperfect image recorded by an instrument can be written as the convolution of the perfect object function with the point spread function (PSF) of the optical system, i.e. its response to a point source. Measuring or estimating the PSF of the system, one can restore, i.e. deconvolve, a high quality image from the measured one 27,28 . The deconvolution operation is known to yield better resolution than the diffraction limit...

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Section: Resultsmentioning

confidence: 99%

Memory-effect based deconvolution microscopy for super-resolution imaging through scattering media

Edrei

Scarcelli

2016

Sci Rep

142

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“…A number of studies on single-parameter estimation have been performed over the past few decades [6], but much attention has begun to be paid to estimation of multiparameters in recent years [7]. Quantum-enhanced sensitivity in simultaneous estimation of multiple phases has been investigated to explain the role of quantum entanglement and identify optimal and realistic setups saturating the ultimate theoretical sensitivity [8][9][10][11][12]. The advantage of exploiting quantum entanglement becomes more significant when sensing takes place in different locations and the parameter of interest is a global feature of the network, e.g., the average of distributed independent phases [13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Optimal distributed quantum sensing using Gaussian states

Lee

Lie

et al. 2020

Phys. Rev. Research

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We find and investigate the optimal scheme of distributed quantum sensing using Gaussian states for estimation of the average of independent phase shifts. We show that the ultimate sensitivity is achievable by using an entangled symmetric Gaussian state, which can be generated using a single-mode squeezed vacuum state, a beam-splitter network, and homodyne detection on each output mode in the absence of photon loss. Interestingly, the maximal entanglement of a symmetric Gaussian state is not optimal although the presence of entanglement is advantageous as compared to the case using a product symmetric Gaussian state. It is also demonstrated that when loss occurs, homodyne detection and other types of Gaussian measurements compete for better sensitivity, depending on the amount of loss and properties of a probe state. None of them provide the ultimate sensitivity, indicating that non-Gaussian measurements are required for optimality in lossy cases. Our general results obtained through a full-analytical investigation will offer important perspectives to the future theoretical and experimental study for distributed Gaussian quantum sensing.

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“…2 , that is a real entity by definition? This is an aspect of the general mathematical/physical phaseretrieval problem [1][2][3][4][5] (or state determination problem [6]), i.e., the characterization of the phase of a general scalar field by its modulus [7,8], not necessarily of quantum nature. Indeed, we have early works of image signal/noise analysis on optical [1,9,10], electronic microscopy and holography [11,12] and, as mentioned in [13], control theory and crystallography.…”

Section: Introductionmentioning

confidence: 99%

Phase-retrieval from Bohm’s equations

2020

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We present an analytic method, based on the Bohmian equations for quantum mechanics, for approaching the phase-retrieval problem in the following formulation: By knowing the probability density |ψ (− → r , t)| 2 and the energy potential V (− → r , t) of a system, how can one determine the complex state ψ (− → r , t)? We illustrate our method with three classic examples involving Gaussian states, suggesting applications to quantum state and Hamiltonian engineering.

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Quantum enhanced phase retrieval

Cited by 14 publications

References 31 publications

Memory-effect based deconvolution microscopy for super-resolution imaging through scattering media

Memory-effect based deconvolution microscopy for super-resolution imaging through scattering media

Optimal distributed quantum sensing using Gaussian states

Phase-retrieval from Bohm’s equations

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