Quantum neuron with real weights.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

This paper proposes a new model of a real weights quantum neuron exploiting the so-called quantum parallelism which allows for an exponential speedup of computations. The quantum neurons were trained in a classical-quantum approach, considering the delta rule to update the values of the weights in an image database of three distinct patterns. We performed classical simulations and also executed experiments in an actual small-scale quantum processor. The results of the experiments show that the proposed quantum real neuron model has a good generalisation capacity, demonstrating better accuracy than the traditional binary quantum perceptron model.

Authors

  • Cláudio A Monteiro
    Centro de Informática, Universidade Federal de Pernambuco, Cidade Universitária, 50670-901, Recife, Pernambuco, Brazil. Electronic address: clam@cin.ufpe.br.
  • Gustavo I S Filho
    Centro de Informática, Universidade Federal de Pernambuco, Cidade Universitária, 50670-901, Recife, Pernambuco, Brazil. Electronic address: gisf@cin.ufpe.br.
  • Matheus Hopper J Costa
    Centro de Informática, Universidade Federal de Pernambuco, Cidade Universitária, 50670-901, Recife, Pernambuco, Brazil. Electronic address: mhjc@cin.ufpe.br.
  • Fernando M de Paula Neto
    Centro de Informática, Universidade Federal de Pernambuco, Cidade Universitária, 50670-901, Recife, Pernambuco, Brazil. Electronic address: fernando@cin.ufpe.br.
  • Wilson R de Oliveira
    Departamento de Estatística e Informática, Universidade Federal Rural de Pernambuco, Dois Irmãos, 52171-900, Recife, Pernambuco, Brazil. Electronic address: wilson.oliveirajr@ufrpe.br.