Modeling and analysis of phase instability in a photonic processor

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.