All-optical implementation of multiple optical transformations through a polarization-encoded diffractive network
AssigneeThe Regents of the University of California
InventorsAydogan Ozcan, Jingxi Li
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AssigneeThe Regents of the University of California
InventorsAydogan Ozcan, Jingxi Li
Estimating the term…
A polarization multiplexed diffractive processor is disclosed that all-optically performs multiple, arbitrarily-selected transformations (e.g., linear) through a single diffractive network trained using deep learning. In this framework, an array of pre-selected linear polarizers is positioned between trainable transmissive diffractive materials that are isotropic, and different target linear transformations (complex-valued) are uniquely assigned to different combinations of input/output polarization states. The transmission layers of this polarization multiplexed diffractive network are trained and optimized via deep learning and error-backpropagation by using thousands of examples of the input/output fields corresponding to each one of the complex-valued linear transformations assigned to different input/output polarization combinations. This polarization-multiplexed all-optical diffractive processor can find various applications in optical computing and polarization-based machine vision tasks.
A polarization-encoded diffractive network comprising:
A method of performing a plurality of optical transformations of a vectorized input optical field using a polarization-encoded diffractive network comprising:
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