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CALIPR: Coherent Addition using Learned Interference Pattern Recognition

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We use machine learning to recognize interference patterns from diffractive coherent beam combinations, to derive a phase error signal for feedback. The scheme is shown in the simulation to be robust against drift during training.

© 2021 The Author(s)

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Poster Presentation

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