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Preprints, Working Papers, ... Year : 2023

Quantum-assisted Adaptive Optics for Microscopy


Adaptive optics (AO) has revolutionized imaging in applications ranging from astronomy to microscopy by enabling the correction of optical aberrations. In label-free microscopes, however, conventional AO methods are limited due to the absence of guidestar and the need to select an optimization metric specific to the type of sample and imaging process being used. Here, we propose a quantum-assisted AO approach that exploits correlations between entangled photons to directly access and correct the point spread function (PSF) of the imaging system. This guidestar-free method is independent of the specimen and imaging modality. We demonstrate the imaging of biological samples in the presence of aberrations using a bright-field imaging setup operating with a source of spatially-entangled photon pairs. We show that our approach performs better than conventional AO in correcting certain types of aberrations, particularly in cases involving significant defocus. Our work improves AO for label-free microscopy, and could play a major role in the development of quantum microscopes, in which optical aberrations can counteract the advantages of using entangled photons and undermine their practical use.

Dates and versions

hal-04199040 , version 1 (07-09-2023)



Patrick Cameron, Baptiste Courme, Daniele Faccio, Hugo Defienne. Quantum-assisted Adaptive Optics for Microscopy. 2023. ⟨hal-04199040⟩
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