Published paper in Optica on March 2019

Efforts to develop quantum computers are motivated by the promise of a tremendous speedup in several computational tasks such as quantum simulation or factoring. A milestone in this quest will be to provide evidence of quantum supremacy, which occurs when a quantum device solves a family of problems faster than state-of-the-art classical computers. The technological race toward this achievement goes hand in hand with the development of classical protocols that can discern genuine quantum processes. Here, we provide a step forward in this direction by presenting a machine-learning algorithm to detect malfunctions within a class of quantum hardware used to demonstrate quantum supremacy, relying only on experimental data.

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