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Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC)

Information Analysis for Quantum Imaging Optimization

Alexander B. Mikhalychev, Ilya Karuseichyk, Svetlana V. Vlasenko, Bänz Bessire, Dmitry A. Lyakhov, Dominik Ludewig Michels, André Stefanov, Dmitri S. Mogilevtsev

Published Jun 21, 2021• 0 citations
Publisher

Abstract

Quantum imaging emerged quite recently as a breakthrough technology of overcoming the diffraction limit in microscopy and enhancement of optical resolution without the necessity to use hard radiation or perform scanning in the near field [1] , [2] . Both, the quantum imaging itself and the more “classical” techniques inspired by it (for example, super-resolution optical fluctuations imaging – SOFI [3] ), rely on detection and analysis of photon (intensity) correlations. Typically, it is believed that the more correlated illuminating light is used and the higher order of the correlations is measured, the larger super-resolution can be achieved. That conclusion is based on efficient narrowing of the point-spread function, which, however, does not necessarily imply better resolution as the ability to reconstruct smaller features of the investigated object successfully.

DOI
10.1109/cleo/europe-eqec52157.2021.9541952

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Quantum imaging emerged quite recently as a breakthrough technology of overcoming the diffraction limit in microscopy and enhancement of optical resolution without the necessity to use hard radiation or perform scanning in the near field [1] , [2] . Both, the quantum imaging itself and the more “classical” techniques inspired by it (for example, super-resolution optical fluctuations imaging – SOFI [3] ), rely on detection and analysis of photon (intensity) correlations. Typically, it is believed that the more correlated illuminating light is used and the higher order of the correlations is measured, the larger super-resolution can be achieved. That conclusion is based on efficient narrowing of the point-spread function, which, however, does not necessarily imply better resolution as the ability to reconstruct smaller features of the investigated object successfully.
Technological advancements in the creation, manipulation and detection of quantum states of light have motivated the application of such states to overcome classical limits in sensing and imaging. In particular, there has been a surge of recent interest in super-resolution imaging based on principles of quantum optics. However, the application of such schemes for practical imaging of biological samples is demanding in terms of signal-to-noise ratio, speed of acquisition and robustness with respect to sample labeling. Here, we re-introduce the concept of quantum image scanning microscopy (Q-ISM), a super-resolution method that enhances the classical image scanning microscopy (ISM) method by measuring photon correlations. Q-ISM was already utilized to achieve super-resolved images of a biological sample labeled with fluorescent nanoscrystals whose contrast is based entirely on a quantum optical phenomenon, photon antibunching. We present here an experimental demonstration of the method and discuss with further details its prospects for application in life science microscopy.
Quantum super-resolution imaging provides a nonlabeling method to surpass the diffraction limit of imaging systems. This technique relies on measurement of the second-order correlation function and usually employs spatially entangled photon sources. We introduce recent methods that achieve spatial resolution enhancement through quantum approaches, particularly the imaging techniques utilizing biphoton states. The fundamental mechanisms are discussed in detail to explain why biphoton states enable super-resolution. Additionally, we introduce multiple algorithms that extract the correlation function from the readings of two-dimensional detectors. Several cases are reviewed to evaluate the advantages and prospects of quantum imaging, along with a discussion of practical developments and potential applications.
Techniques of optical superresolution imaging are vital for uncovering the complex dynamics of biochemistry in cellular environments. However the practical resolution for superresolution imaging is limited by the increased photon budget for superresolution, compared with conventional microscopy. For this reason it is important to determine the optimal methods for analysing all of the incoming information. Most approaches to microscopy use only the wave-like properties of light, but the particle-like nature of light provides extra information that is normally inaccessible and can be used to increase imaging resolution. Here we theoretically study the localisation of quantum emitters using higher-order quantum correlation functions to understand the resolution that is practically achievable for bio-imaging tasks. We show explicit imaging results for varying number of emitters as a function of correlation order to illustrate the necessary tradeoffs between imaging resolution and acquisition time.
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Reaching high-resolution imaging of delicate samples at a low-intensity level is a major challenge in microscopy. Here, we present and experimentally implement an advanced quantum super-resolution imaging technique based on photon statistics measurement. Our reconstruction algorithm adapts to any kind of non-Poissonian emitters, outperforming the corresponding classical SOFI method, in particular in low-light conditions. It offers sub-diffraction resolution improvement that scales with the j , where j is the highest-order central moments of the photocounts. More remarkably, we show that in combination with structured illumination, an improvement of j + j can be reached, providing a promising avenue for non-invasive super-resolution microscopy.