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    Area of Science:

    • Photonics
    • Scientific Computing
    • Numerical Analysis

    Background:

    • Photonic computing offers speed and energy advantages but faces accuracy limitations due to analog signal bitwidth.
    • Developing robust photonic primitives is crucial for realizing the full potential of optical computation.

    Purpose of the Study:

    • To demonstrate a configurable, fixed-point coherent photonic iterative solver for numerical eigenvalue problems.
    • To address the inaccuracy issues inherent in analog photonic computing.

    Main Methods:

    • Utilized shifted inverse iteration for the photonic iterative solver.
    • Implemented a photonic primitive capable of handling arbitrarily sized sparse matrix-vector multiplication.
    • Applied the solver to determine eigenmodes within a photonic waveguide structure.

    Main Results:

    • Successfully demonstrated a fixed-point coherent photonic iterative solver.
    • The solver accommodates large-scale sparse matrix-vector multiplication.
    • Eigenmodes of a photonic waveguide structure were accurately computed.

    Conclusions:

    • The photonic iterative eigensolver avoids error accumulation across iterations.
    • This work presents a viable approach for implementing complex scientific computing tasks on photonic hardware.
    • Enables accurate and efficient eigenvalue problem solving using photonic integrated circuits.