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Improved REV algorithm based on signal reconstruction for phase calibration of optical phased array.

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    A new hybrid algorithm calibrates optical phased array (OPA) chips by integrating signal reconstruction, rotating-element electric-field vector (REV) techniques, and quantum particle swarm optimization (QPSO). This method improves far-field beam quality and achieves superior side lobe suppression compared to other algorithms.

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    Area of Science:

    • Photonics and Optical Engineering
    • Beam Control Systems
    • Signal Processing

    Background:

    • Optical phased arrays (OPAs) are crucial for non-mechanical beam control.
    • Initial phase offsets in OPA chips significantly degrade far-field beam quality.
    • Effective calibration is essential for optimal OPA performance.

    Purpose of the Study:

    • To develop a novel hybrid algorithm for calibrating OPA chips.
    • To address the challenge of initial phase offsets in OPA systems.
    • To enhance the quality of far-field beams generated by OPAs.

    Main Methods:

    • A hybrid algorithm integrating signal reconstruction, rotating-element electric-field vector (REV) techniques, and quantum particle swarm optimization (QPSO).
    • Application of the proposed algorithm to calibrate a 512-channel OPA chip.
    • Comparative analysis against basic particle swarm optimization (BPSO) and deterministic stochastic gradient descent (DSGD).

    Main Results:

    • The proposed hybrid algorithm effectively calibrates OPA chips.
    • Demonstrated ability to escape local optima during the calibration process.
    • Achieved a higher side lobe suppression ratio compared to BPSO and DSGD under similar iteration counts.

    Conclusions:

    • The novel hybrid algorithm offers a robust solution for OPA chip calibration.
    • The method significantly improves far-field beam quality by mitigating phase offset issues.
    • QPSO-enhanced calibration provides superior performance in side lobe suppression for OPA systems.