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    This study introduces a novel phase retrieval algorithm for Hanbury Brown-Twiss imaging. It effectively handles noisy coherence data, significantly reducing imaging time and improving image quality.

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    Area of Science:

    • Optics and Photonics
    • Quantum Imaging
    • Signal Processing

    Background:

    • Traditional Hanbury Brown-Twiss (HBT) imaging separates coherence magnitude estimation and image construction.
    • This two-step approach is sensitive to noise in coherence measurements.
    • Significant imaging time is often required to achieve acceptable signal-to-noise ratios.

    Purpose of the Study:

    • To develop a unified phase retrieval algorithm for HBT imaging.
    • To improve image quality in the presence of high noise levels in coherence magnitude data.
    • To drastically reduce the required imaging time for HBT measurements.

    Main Methods:

    • A novel unified formulation for phase retrieval in HBT imaging.
    • Simultaneous estimation of measurement noise and image reconstruction.
    • Leveraging interrelations between coherence data, image, and noise constraints.

    Main Results:

    • High-quality image reconstruction achieved from significantly noisy coherence magnitude data.
    • Successful estimation of measurement noise alongside image data.
    • Demonstrated reduction in necessary imaging time by several orders of magnitude.

    Conclusions:

    • The unified algorithm offers a robust solution for noisy HBT imaging.
    • This approach enhances efficiency and image fidelity in HBT-based imaging techniques.
    • The method has the potential to accelerate scientific discovery in fields utilizing HBT interferometry.