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Transverse mode characterization in optical fibers using singular value decomposition.

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    This study introduces a novel data-driven method to experimentally determine optical fiber transverse modes. The approach uses singular value decomposition to identify the fiber's modal base set, offering a versatile solution for any fiber type.

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    Area of Science:

    • Optics and Photonics
    • Materials Science

    Background:

    • Characterizing transverse modes in optical fibers is crucial for understanding light propagation.
    • Existing experimental methods often have limitations regarding fiber length or size.

    Purpose of the Study:

    • To propose a new scalar and data-driven experimental approach for characterizing optical fiber transverse modes.
    • To demonstrate the method's ability to retrieve the orthogonal modal base set of a fiber.

    Main Methods:

    • Collecting extensive data under varied coupling conditions.
    • Applying singular value decomposition (SVD) to the collected dataset.
    • Utilizing a scalar, data-driven approach for mode retrieval.

    Main Results:

    • The proposed method successfully retrieves the orthogonal modal base set.
    • Experimental results show strong agreement with simulated transverse modes.
    • The approach is independent of fiber length and size.

    Conclusions:

    • The developed scalar, data-driven method provides an effective experimental technique for optical fiber transverse mode characterization.
    • This approach offers a significant advantage due to its applicability to any fiber, irrespective of physical dimensions.
    • The method's versatility makes it a valuable tool for optical fiber research and development.