Speaker: Dario Gerace (University of Pavia)


We introduce a quantum information-based algorithm implementing the quantum computer version of the classical Rosenblatt’s perceptron, the simplest implementation of an artificial neuron. We show exponential advantage in encoding resources over alternative realizations, and experimentally test a few qubits version of this model on the IBM  quantum processor available for cloud quantum computing, which gives remarkably good answers against the expected results. As a first step towards practical realization of artificial quantum neural networks, we show that our quantum model of a perceptron can be used as an elementary nonlinear classifier of simple patterns.