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arXiv:1609.08741 · Light Science & Applications

Digital spiral object identification using random light

Zhe Yang, Omar S. Magaña‐Loaiza, Mohammad Mirhosseini, Yiyu Zhou, Boshen Gao, Lu Gao, Seyed Mohammad Hashemi Rafsanjani, Gui‐Lu Long, Robert W. Boyd

Published Feb 15, 2017• 68 citations
arXivHTMLPDF

Abstract

Photons that are entangled or correlated in orbital angular momentum have been extensively used for remote sensing, object identification and imaging. It has recently been demonstrated that intensity fluctuations give rise to the formation of correlations in the orbital angular momentum components and angular positions of random light. Here we demonstrate that the spatial signatures and phase information of an object with rotational symmetries can be identified using classical orbital angular momentum correlations in random light. The Fourier components imprinted in the digital spiral spectrum of the object, as measured through intensity correlations, unveil its spatial and phase information. Sharing similarities with conventional compressive sensing protocols that exploit sparsity to reduce the number of measurements required to reconstruct a signal, our technique allows sensing of an object with fewer measurements than other schemes that use pixel-by-pixel imaging. One remarkable advantage of our technique is that it does not require the preparation of fragile quantum states of light and operates at both low- and high-light levels. In addition, our technique is robust against environmental noise, a fundamental feature of any realistic scheme for remote sensing.

DOI
10.1038/lsa.2017.13

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Photons that are entangled or correlated in orbital angular momentum have been extensively used for remote sensing, object identification and imaging. It has recently been demonstrated that intensity fluctuations give rise to the formation of correlations in the orbital angular momentum components and angular positions of random light. Here we demonstrate that the spatial signatures and phase information of an object with rotational symmetries can be identified using classical orbital angular momentum correlations in random light. The Fourier components imprinted in the digital spiral spectrum of the object, as measured through intensity correlations, unveil its spatial and phase information. Sharing similarities with conventional compressive sensing protocols that exploit sparsity to reduce the number of measurements required to reconstruct a signal, our technique allows sensing of an object with fewer measurements than other schemes that use pixel-by-pixel imaging. One remarkable advantage of our technique is that it does not require the preparation of fragile quantum states of light and operates at both low- and high-light levels. In addition, our technique is robust against environmental noise, a fundamental feature of any realistic scheme for remote sensing.
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Using spontaneous parametric down-conversion as a source of correlated photon pairs, correlations are measured between the orbital angular momentum (OAM) in a target beam (which contains an unknown object) and that in an empty reference beam. Unlike previous studies, the effects of the object on off-diagonal elements of the OAM correlation matrix are examined. Because of the presence of the object, terms appear in which the signal and idler OAM do not add up to that of the pump. Using these off-diagonal correlations, the potential for high-efficiency object identification by means of correlated OAM states is experimentally demonstrated for the first time. The higher-dimensional OAM Hilbert space enhances the information capacity of this approach, while the presence of the off-diagonal correlations allows for recognition of specific spatial signatures present in the object. In particular, this allows the detection of discrete rotational symmetries and the efficient evaluation of multiple azimuthal Fourier coefficients using fewer resources than in conventional pixel-by-pixel imaging. This represents a demonstration of sparse sensing using OAM states, as well as being the first correlated OAM experiment to measure properties of a real, stand-alone object, a necessary first step toward correlated OAM-based remote sensing.
The concept of correlated two-photon spiral imaging is introduced. We begin by analyzing the joint orbital angular momentum (OAM) spectrum of correlated photon pairs. The mutual information carried by the photon pairs is evaluated, and it is shown that when an object is placed in one of the beam paths the value of the mutual information is strongly dependent on object shape and is closely related to the degree of rotational symmetry present. After analyzing the effect of the object on the OAM correlations, the method of correlated spiral imaging is described. We first present a version using parametric down-conversion, in which entangled pairs of photons with opposite OAM values are produced, placing an object in the path of one beam. We then present a classical (correlated, but nonentangled) version. The relative problems and benefits of the classical versus entangled configurations are discussed. The prospect is raised of carrying out compressive imaging via two-photon OAM detection to reconstruct sparse objects with few measurements.
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Spiral holographic imaging in the Hong-Ou–Mandel interference scheme is introduced. Using spontaneous parametric down-conversion as a source of photon pairs, we analyze the joint orbital angular momentum spectrum of a reference photon and the photon encoding information of the object. The first-order interference of light beams in standard holographic imaging is replaced by the quantum interference of two-photon probability amplitudes. The difficulty in retrieving the amplitude and phase structure of an unknown photon is thereby avoided as classical interferometric techniques such as optical holography do not apply. Our results show that the full information of the object's transmission function can be recorded in the spiral hologram, which originates directly from the joint orbital angular momentum spectrum. This presents a lateral demonstration of compressive imaging and can potentially be used for remote sensing.