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Related Experiment Video

Updated: Jun 11, 2026

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
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Phase-gradient information from vortex encoders.

Altai Perry, Luat T Vuong

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    |June 10, 2026
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    Summary
    This summary is machine-generated.

    Coded diffraction imaging reconstructs complex fields using phase-less sensors. A topological phase singularity in diffractive masks enhances phase gradient retrieval, improving reconstruction quality and guiding hybrid computing strategies.

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    Last Updated: Jun 11, 2026

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    Area of Science:

    • Optics and Photonics
    • Computational Imaging
    • Machine Learning

    Background:

    • Coded diffraction enables complex field reconstruction from intensity-only sensor images.
    • Reconstruction quality is sensitive to object-encoder design and sensor data sampling.

    Purpose of the Study:

    • To derive the Fisher information content of image phase gradients using topological phase singularities.
    • To numerically validate machine-learned phase gradient retrieval for improved diffractive imaging.

    Main Methods:

    • Derivation of Fisher information for phase gradients with topological phase singularities.
    • Numerical validation using simple neural networks for phase gradient retrieval.
    • Analysis of sampling effects and information traceability in Fourier-plane diffractive encoding.

    Main Results:

    • A topological phase singularity enhances the capture of phase gradient information.
    • Machine learning effectively retrieves phase gradients from sensor patterns.
    • Identified critical sampling issues and information traceability challenges in the encoder scheme.

    Conclusions:

    • Topological phase singularities offer a pathway to improved phase gradient information in coded diffraction.
    • Information-guided strategies are crucial for optimizing hybrid computing in diffractive imaging.
    • Addressing sampling and traceability is key for robust phase retrieval.