
AI Deciphers Quantum Light Signals with Record Accuracy
Researchers have successfully employed deep learning to classify quantum emission signals from tungsten disulfide nanobubbles. By converting these signals into images using wavelet transforms, the VGG16 model achieved an impressive 99.4% accuracy, paving the way for advancements in quantum cryptography and photonics.






















