A Multi-Layer Topologically Reconfigurable Broadcast-and-Weight Photonic Neural Network

Broadcast-and-weight (BaW) photonic neural networks can process high-bandwidth signals with limited chip area, but they traditionally lack topological reconfigurability. We propose using a fully-connected recurrent BaW system as a topologically reconfigurable network and demonstrate a multi-layer feedforward network implemented on such a system.