Binary-spot-mapped single-layer diffractive network via region-based energy routing for all-optical OAM mode...

Orbital angular momentum (OAM) mode classification is challenging for single-layer phase-only diffractive neural networks due to the complex phase structure and spatially extended energy distribution of OAM beams, which are difficult to map into well-separated continuous output patterns under limited modulation degrees of freedom. To address this mismatch, we propose a binary-spot-mapped single-layer diffractive neural network (BS-D2NN) to realize region-based energy routing for OAM mode classification, which provides a compact all-optical energy-routing solution with low system complexity and direct region-based optical readout. Experimental results show that the proposed BS-D2NN achieves an overall classification accuracy of 93.89% under turbulence-free conditions, while effectively routing optical energy into class-specific target regions for mode classification and spatial demultiplexing. Supplementary experiments further indicate that the same framework remains applicable under turbulence conditions through condition-specific retraining, without changing the underlying network architecture or optimization principle.