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    Area of Science:

    • Optical Physics
    • Fiber Optics
    • Metrology

    Background:

    • Speckle patterns in multimode fibers (MMF) offer valuable light information.
    • Traditional speckle-based spectrometers/wavemeters often rely on costly and slow cameras.
    • Limitations of cameras hinder applications in optical communications, metrology, and sensing.

    Purpose of the Study:

    • To develop a cost-effective and robust wavemeter using fiber optics.
    • To overcome the limitations of camera-based speckle analysis.
    • To enhance wavelength measurement capabilities for optical sensing and metrology.

    Main Methods:

    • Fused a seven-core fiber (SCF) with an MMF to capture speckle patterns.
    • Utilized SCF's space division multiplexing with an optical switch for diverse speckle generation.
    • Employed a convolutional neural network (CNN) regression algorithm for speckle data analysis.

    Main Results:

    • Achieved high wavelength resolution, resolving adjacent wavelengths of 1 pm.
    • Demonstrated a low measurement error of approximately 0.2 pm.
    • Investigated the impact of MMF length on wavelength resolution.

    Conclusions:

    • Presented a robust and cost-effective wavelength measurement device.
    • Successfully utilized SCF and CNN for advanced speckle analysis.
    • The proposed method offers a viable alternative to camera-based systems for optical sensing.