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    This study models phase instability in reconfigurable multimode interferometers for quantum information processing. The developed models accurately predict and correct phase fluctuations, enhancing photonic processor stability.

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    Area of Science:

    • Integrated photonics
    • Quantum information processing
    • Optical computing

    Background:

    • Reconfigurable multimode interferometers are crucial for large-scale optical quantum information processing.
    • Maintaining phase stability in multiport signals is a key challenge due to active cooling and temperature drifts.
    • Existing photonic processors face limitations in signal stability for complex quantum operations.

    Purpose of the Study:

    • To develop theoretical models for simulating phase instability in photonic processors.
    • To validate these models against experimental data.
    • To apply the models for input phase correction in photonic processors.

    Main Methods:

    • Theoretical modeling using Brownian random walk.
    • Phase reconstruction based on experimentally observed oscillating harmonics.
    • Experimental validation and application for self-feedback control.

    Main Results:

    • The proposed models accurately simulate phase instability in photonic processors.
    • Experimental validation confirmed the model's predictive capabilities.
    • The models were successfully applied to correct input phase fluctuations.

    Conclusions:

    • Theoretical modeling is effective for understanding and mitigating phase instability in reconfigurable multimode interferometers.
    • The developed models provide a pathway for enhancing the stability of photonic processors for quantum information processing.
    • Self-feedback control based on these models can improve the performance of optical quantum information systems.