3 papers
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.app-ph2026
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…
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…