ML-based approach to classification and generation of structured light propagation in turbulent media

arXiv:2604.14208v2 Announce Type: replace-cross Abstract: We study the classification task of structured-light beams after propagation through a random turbulent medium. The received speckle patterns are generated by numerical simulation of a stochastic paraxial propagation model, and the classification task is formulated over a finite alphabet of 15 OAM source classes. We benchmark intensity and autocorrelation inputs using SimpleCNN and ResNet-18 as classifiers. We also quantify the effect of training-set size and receiver-window misalignment. Since additional propagated samples may be costl

Source: arXiv cs.LG — read the full report at the original publisher.

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