Neural-network approach for identifying nonclassicality from click-counting data
Valentin Gebhart, Martin Bohmann · Physical Review Research · 2020
This work uses the supervised learning of a deep neural network to identify nonclassicality of light detected through multiplexed measurement schemes. The network learns to correctly classify different classical and nonclassical states, outperforms other indicators of nonclassicality for a wide parameter range and also identifies nonclassicality for states outside the training set.