Brunello Tirozzi (University of Rome)
Title: Quantum neural networks, an immersion of classical neural networks in the domain of quantum computing
Abstract: Neural networks arise as an intersection of different disciplines, neurobiology, computer technology and statistical mechanics. The retrieval and storage of information have been studied by the specialists of these fields for many decades and many interesting point of view and approaches have been exchanged with success for getting interesting results. In particular neurobiological descriptions have been incorporated in the well known Hopfield model which has been solved exactly with the cavity method. The difference with classical statistical mechanics is that the Hopfield model is a mean field theory of classical spins interacting through random interactions, the randomness being given by the stored patterns. In the first part of the talk I will describe the methods and aims of this classical approach. In the second part I will explain how to transfer this machinery in the field of quantum computing, give the main definitions and illustrate how to estimate the states of minimum energy of the quantum neural network.