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Vector-vortex beam identification via optical correlation using deconvolution-derived filter design
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DOI：10.1016/j.optlastec.2026.114785.png)
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Vector-vortex beams, characterized by phase and polarization singularities, are widely used in the domains of communication, sensing, quantum optics, and many more. Successful implementation of vector-vortex beams requires fast and efficient detection, along with characteristic feature extraction. By leveraging the fast information processing capabilities of an optical correlator, we propose a correlation-based identification technique for the topological charge and type of a vector-vortex beam. The proposed technique utilizes a deconvolution-derived correlation filter, which can carry information about multiple training functions. The method is demonstrated for Gaussian, Laguerre-Gaussian, and Bessel-Gaussian vector-vortex beams. With observed simulation and experimental outcomes, the vector-vortex beam identification technique is validated. Through the fabrication of ideal correlation outputs, the proposed technique efficiently identifies the input vector-vortex beam by locating the correlation peak. The identification capability of the proposed technique highlights the potential of a real-time classification system for versatile applications, paving the way for the development of an efficient vector-vortex beam identification device.
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