Approaching graph problems with continuous variable quantum computing

Abstract

We introduce a method for solving the Max-Cut problem using a variational algorithm and a continuous-variables quantum computing approach. The quantum circuit consists of two parts: the first one embeds a graph into a circuit using the Takagi decomposition and the second is a variational circuit which solves the Max-Cut problem. We analyze how the presence of different types of non-Gaussian gates influences the optimization process by performing numerical simulations. We also propose how to treat the circuit as a machine learning model.