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This review establishes a theoretical framework for passive optical superresolution that surpasses the classical diffraction limit by leveraging quantum measurement strategies. By optimizing detection schemes to minimize noise inherent in the quantum nature of light, these methods enable precise localization and classification of sub-Rayleigh sources previously considered inaccessible. The work bridges advanced quantum estimation theory with practical applications in microscopy, astronomy, and optical sensing, marking a significant step toward quantum-limited imaging systems.
Passive optical superresolution at the quantum limit
arXiv:2605.10767v2 Announce Type: replace Abstract: 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.
Abstract: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.
Quantum Physics (quant-ph); Optics (physics.optics)
arXiv:2605.10767 [quant-ph]
(or arXiv:2605.10767v2 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2605.10767 Focus to learn more arXiv-issued DOI via DataCite
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