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arXiv:1806.02781 · Physical Review A

Quantum limit to subdiffraction incoherent optical imaging

Mankei Tsang

Published Jan 3, 2019• 91 citations
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Abstract

The problem of finding the fundamental resolution of an optical system can be cast in terms of a quantum estimation problem. Here an upper bound on the quantum Fisher Information for the moments of an arbitrary subdiffraction object is derived, establishing a criterion of resolution for far-field incoherent imaging.
DOI
10.1103/physreva.99.012305

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In a previous paper [M. Tsang, Phys. Rev. A 99, 012305 (2019)], I proposed a quantum limit to the estimation of object moments in subdiffraction incoherent optical imaging. In this sequel, I prove the quantum limit rigorously by infinite-dimensional analysis. A key to the proof is the choice of an unfavorable parametric submodel to give a bound for the semiparametric problem. By generalizing the quantum limit for a larger class of moments, I also prove that the measurement method of spatial-mode demultiplexing with just one or two modes is able to achieve the quantum limit. For comparison, I derive a classical bound for direct imaging using the parametric-submodel approach, which suggests that direct imaging is substantially inferior.
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For more than a century, the diffraction limit has defined the resolution achievable by passive optical imaging systems. Although some resolution improvement can be gained through classical data processing of the image, it is limited by the noise arising from quantum nature of light. Minimizing the effect of this noise requires quantum treatment of optical imaging. By reformulating imaging as a problem of quantum measurement and estimation, it becomes possible to identify optimal detection strategies that recover spatial information previously thought inaccessible. This review summarizes the theoretical framework that underpins this development, from the formulation of quantum Cramer-Rao bounds and Chernoff bounds to the construction of receivers that attain them, such as those based on spatial-mode demultiplexing. We show how these methods can beat conventional imaging in the classification, localization, and imaging of sub-Rayleigh incoherent sources. We then discuss extensions to multiparameter and partially coherent scenarios, and highlight the unifying connections between estimation and discrimination tasks. Finally, we survey recent experimental demonstrations that approach quantum-limited resolution and outline emerging applications in microscopy, astronomy, and optical sensing.
I derive classical and quantum lower error bounds for moment estimation in subdiffraction incoherent optical imaging. While the end results are similar to earlier ones [Tsang, Phys. Rev. Res. 1, 033006 (2019); Phys. Rev. A 99, 012305 (2019)], the present work avoids the flawed mathematical assumptions in the earlier works by adopting a parametric-submodel approach from semiparametric statistics. With the rigorous bounds at hand and redefining the parameter of interest, I show that an alternative measurement called spatial-mode demultiplexing (SPADE) is superior to ideal direct imaging for a subdiffraction object, even if SPADE can measure only a finite number of modes.
As a method to extract information from optical systems, imaging can be viewed as a parameter estimation problem. The fundamental precision in locating one emitter or estimating the separation between two incoherent emitters is bounded below by the multiparameter quantum Cramér-Rao bound (QCRB). Multiparameter QCRB gives an intrinsic bound in parameter estimation. We determine the ultimate potential of quantum-limited imaging for improving the resolution of a far-field, diffraction-limited optical field within the paraxial approximation. We show that the quantum Fisher information matrix (QFIm) in about one emitter’s position is independent on its true value. We calculate the QFIm of two unequal-brightness emitters’ relative positions and intensities; the results show that only when the relative intensity and centroids of two-point sources, including longitudinal and transverse directions, are known exactly, the separation in different directions can be estimated simultaneously with finite precision. Our results give the upper bounds on certain far-field imaging technology and will find wide use in applications from microscopy to astrometry.