Massively parallel universal linear transformations using a wavelength-multiplexed diffractive optical network

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Massively parallel universal linear transformations using a wavelength-multiplexed diffractive optical network
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Deeplearning-designed diffractive processor computes hundreds of transformations in parallel SPIEtweets

separate monochromatic diffractive networks is not a feasible strategy that can compete with a wavelength-multiplexed design.

This, once again, highlights the significance of our wavelength multiplexing scheme: a wavelength-multiplexed diffractive optical network can be realized through the engineering of the surface profiles of dielectric diffractive layers with arbitrary dispersion properties, whereas these profiles should be designed by simultaneously taking into account all theTo the best of our knowledge, there has not been a demonstration of a design for the all-optical implementation of a complex-valued,...

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