Continuous Variables Quantum Neural Networks

Abstract

Quantum mechanics in conjunction with continuous variables systems are promising for artificial neural networks in terms of information processing and real data domains. For classical simulation concerns, a brand-new continuous variables quantum neural network (QNN) was implemented, analyzed and tested keeping the affinity with quantum hardware. The simulated QNN approach is based on second statistical moments of the system’s Gaussian stage jointly with expectation value expressions acting as the non-Gaussian evolution and measurement of the system. The required components, infrastructure and algorithms were described and developed along with its relative demonstrations giving a complete traceability of the proposed quantum neural network model supported with illustrative examples.