A surrogate matrix-space training stage followed by adjoint-based physical realization allows scalable design of photonic neural networks that match ideal accuracy on image tasks with orders-of-magnitude fewer electromagnetic simulations.
All-optical machine learning using diffractive deep neural networks
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The roadmap reviews advances in generating and manipulating high-dimensional quantum states of light across photonic degrees of freedom and outlines common challenges for their integration into future quantum technologies.
citing papers explorer
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Scalable Photonic Neural Networks via Surrogate Scattering-Matrix Inverse Design
A surrogate matrix-space training stage followed by adjoint-based physical realization allows scalable design of photonic neural networks that match ideal accuracy on image tasks with orders-of-magnitude fewer electromagnetic simulations.
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High-Dimensional Quantum Photonics: Roadmap
The roadmap reviews advances in generating and manipulating high-dimensional quantum states of light across photonic degrees of freedom and outlines common challenges for their integration into future quantum technologies.