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We consider a model of an artificial neural network that usesquantum-mechanical particles in a two-humped potential as a neuron. To simulatesuch a quantum-mechanical system the Monte-Carlo integration method is used. Aform of the self-potential of a particle and two potentials (exciting andinhibiting) interaction are proposed. The possibility of implementing thesimplest logical elements, (such as AND, OR and NOT) based on introducedquantum particles is shown. Further we show implementation of a simplestconvolutional network. Finally we construct a network that recognizeshandwritten symbols, which shows that in the case of simple architectures, itis possible to transfer weights from a classical network to a quantum one.

Artificial Quantum Neural Network: quantum neurons, logical elements and tests of convolutional nets