5 papers
Inverse-designed meta processing units for multi-task near-field photonic computing
Chu Wu, Zeyu Cai, Songtao Yang +5
Integrated photonic neural networks require optical operators that are simultaneously compact, matrix-general and compatible with task-level reconfigurability. Here we introduce a…
3D aperture-engineered diffractive neural networks for super-resolution electromagnetic wave computing
Sheng Gao, Songtao Yang, Haiou Zhang +2
The rapid progress in 6G communication and high-bandwidth radar has driven an unprecedented surge in the spatial density of signal sources, resulting in an increasingly congested e…
Meta-training of diffractive meta-neural networks for super-resolution direction of arrival estimation
Songtao Yang, Sheng Gao, Chu Wu +3
Diffractive neural networks leverage the high-dimensional characteristics of electromagnetic (EM) fields for high-throughput computing. However, the existing architectures face cha…
Roadmap on Neuromorphic Photonics
Daniel Brunner, Bhavin J. Shastri, Mohammed A. Al Qadasi +147
This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementatio…
Super-resolution imaging using super-oscillatory diffractive neural networks
Hang Chen, Sheng Gao, Zejia Zhao +4
Optical super-oscillation enables far-field super-resolution imaging beyond diffraction limits. However, the existing super-oscillatory lens for the spatial super-resolution imagin…