A Physics-Aware Simulation Platform for Phase-Only Optical Neural Networks
Linqi Xiao, Muhammad Ridwanur Rahim, Peter Tso, Rongqing Hui, Andrea Fumagalli · 2025
A physics-aware simulation platform is proposed for optical neural networks (ONNs), incorporating phase-only modulation and passive free-space propagation. The platform enables end-to-end training under experimentally realistic constraints, with both the phase mask and propagation distance treated as learnable parameters. To facilitate classification, structured 2D output patterns are introduced, where each label corresponds to a fixed spatial light spot. When evaluated with the MNIST dataset, the system achieves 94.6% accuracy using a single phase modulation layer, demonstrating the effectiveness of spatial encoding in physically plausible ONNs.