Approaching graph problems with continuous variable quantum computing

2019/06/17 by Michał Stęchły, Stęchły, Michał, Ntwali Toussaint Bashige +4
Computer Science · Physics and Astronomy · #Neural Networks and Reservoir Computing #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #quant-ph

paper · pdf · doi:10.48550/arxiv.1906.07047

arxiv created 2019/06/17 · arxiv updated 2019/06/18

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.

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