Deep learning-driven phase calibration methodology for enhanced beamforming in integrated optical phased array

We introduce a novel approach leveraging a deep neural network architecture for precise phase calibration in a 64-channel integrated optical phased array. Experimental results demonstrate its high predictive accuracy and phase calibration performance, which are comparable to conventional optimization-based algorithms across the multiple beam directions.