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Extending the Processing Power of Optical Computing

Modern neural networks mostly use linear operations like convolutions and matrix-vector multiplications. Although there are specialist processors for these tasks, like as GPUs and TPUs, their power and bandwidth are limited.

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UCLA achieves optical computing boost with diffractive network advance

Performing complex-valued linear transformations using spatially incoherent diffractive optical networks

Performing complex-valued linear transformations using spatially incoherent diffractive optical networks
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Diffractive Network Advance Boosts Optical Computing

Diffractive Network Advance Boosts Optical Computing
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Diffractive optical network enables multispectral quantitative phase imaging in a snapshot

Diffractive optical network enables multispectral quantitative phase imaging in a snapshot
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