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physics.optics2026
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…
physics.optics2025
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…
physics.optics2024
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…