  Recently integrated optics has become an intriguing platform for implementing
machine learning algorithms and inparticular neural networks. Integrated
photonic circuits can straightforwardly perform vector-matrix
multiplicationswith high efficiency and low power consumption by using
weighting mechanism through linear optics. Although,this can not be said for
the activation function which requires either nonlinear optics or an
electro-optic module withan appropriate dynamic range. Even though all-optical
nonlinear optics is potentially faster, its current integrationis challenging
and is rather inefficient. Here we demonstrate an electro-absorption modulator
based on an IndiumTin Oxide layer, whose dynamic range is used as nonlinear
activation function of a photonic neuron. The nonlinearactivation mechanism is
based on a photodiode, which integrates the weighed products, and whose
photovoltage drivesthe elecro-absorption modulator. The synapse and neuron
circuit is then constructed to execute a 200-node MNISTclassification neural
network used for benchmarking the nonlinear activation function and compared
with an equivalentelectronic module.
