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    Approach Uses Artificial Intelligence to Predict Quantum Advantage

    Article obtained from Photonics RSS Feed.

    Researchers from the Moscow Institute of Physics and Technology (MIPT), Valiev Institute of Physics and Technology, and ITMO University created a neural network that learned to predict the behavior of a quantum system by “looking” at its network structure. This convolutional neural network (CNN) is designed specifically to learn from graphs. It can autonomously predict which network solutions will demonstrate quantum advantage.

    On a graph, a quantum walk — an advanced tool for constructing quantum algorithms — is fundamentally different from a random (classical) walk. On some graphs, quantum walks are faster than their classical analogs. When they are faster, quantum walks can enable quantum algorithmic…

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    Feb, 10 2020 |

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