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Single-shot polarimetry of vector beams by supervised learning

Davide Pierangeli, Claudio Conti

Nature Communications · 2023

Research context

States of light encoding multiple polarizations - vector beams - offer unique capabilities in metrology and communication. However, their practical application is limited by the lack of methods for measuring many polarizations in a scalable and compact way. Here we demonstrate polarimetry of vector beams in a single shot without any polarization optics. We map the beam polarization content into a spatial intensity distribution through light scattering and exploit supervised learning for single-shot measurements of multiple polarizations. We characterize structured light encoding up to nine polarizations with accuracy beyond 95% on each Stokes parameter. The method also allows us to classify beams with an unknown number of polarization modes, a functionality missing in conventional techniques. Our findings enable a fast and compact polarimeter for polarization-structured light, a general tool that may radically impact optical devices for sensing, imaging, and computing.

Keywords: Polarimetry, Shot (pellet), Computer science, Single shot, One shot, Artificial intelligence, Optics, Physics, Materials science, Engineering, Scattering, Metallurgy, Mechanical engineering

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29 citations · OpenAlex · observed 2026-09-08

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Article https://doi.org/10.1038/s41467-023-37474-0 Single-shot polarimetry of vector beams by supervised learning Davide Pierangeli 1,2 & Claudio Conti 2,3 States of light encoding multiple polarizations - vector beams - offer unique capabilities in metrology and communication. However, their practical appli- cation is limited by the lack of methods for measuring many polarizations in a scalable and compact way. Here we demonstrate polarimetry of vector beams in a single shot without any polarization optics. We map the beam polarization content into a spatial intensity distribution through light scattering and exploit supervised learning for single-shot measurements of multiple polarizations. We characterize structured light encoding up to nine polarizations with accuracy beyond 95% on each Stokes parameter. The method also allows us to classify beams with an unknown number of polarization modes, a functionality missing in conventional techniques. Our findings enable a fast and compact polarimeter for polarization-structured light, a general tool that may radically impact optical devices for sensing, imaging, and computing. Generating, manipulating, and detecting the optical state of polariza- tion (SOP) is of paramount importance in many areas, such as optical communication1, sensing2, microscopy3, and quantum information and computation4. While progress in material growth and nano- technology are enabling advances in active polarization control5–7, the measurement of light polarization remains limited by its intrinsic vectorial nature. Complete determination of a single SOP needs at least four individual measurements, each projecting the state on a distinct vector8–10. Conventional polarimetry methods replicate in time or space the polarization analyzer, which results in bulky optical setups, or in costly compact polarimeters based on metasurfaces11–18. While for uniformly-polarized light the need for several measurements is still affordable and can be mitigated by using specific optical devices19, it becomes a serious issue for beams with a spatial polarization structure. Light with non-uniform polarization across the transverse plane exhibits non-separable correlations between polarization and spatial modes20.

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Cite / 引用

Davide Pierangeli, Claudio Conti. Single-shot polarimetry of vector beams by supervised learning. Nature Communications (2023). https://doi.org/10.1038/s41467-023-37474-0

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